Hi all,

I just got invited to the HackerRank online assessment for a Data Scientist II role at QuantumBlack (McKinsey), based in Canada. The invite says it could include coding, data modelling, technical knowledge or Excel exercises, and mine is 90 minutes long, so I’m trying to get a sense of what fits into that time.

For anyone who’s taken it recently:

• What was the format? How many questions, and what split between SQL, Python and multiple choice?
• Was there a modelling task, and if so, what kind (classification, regression, time series)? Was scikit-learn available?
• How was the time pressure in the 90 minutes? Did you finish everything?
• Was it proctored (webcam or screen sharing)?
• Can we look up syntax through the Hackerrank platform?

• Any surprises or things you wish you’d practised more?

  Thanks in advance, and happy to share my experience afterwards!

About the Role

The Data Scientist, Product Growth and Experimentation will help drive decision making in support of our Product Led Growth function.

This role sits at the intersection of Data, Product, Growth, and GTM. You will work deeply embedded within the Product and Engineering teams focused on PLG. Your focus will be illuminating the user journey from initial interest to fully adopted and all the steps in between. You will surface friction points in the onboarding process and identify behaviors that are indicative of successful adoption. You will evaluate interventions that help us to bring the value of Temporal to more users.

You will work effectively across both large data, clean data sets and data sets with constraints in duration and sample size to provide well-informed recommendations and conclusions. You will bring deep knowledge and practical experience with statistical methods including matched comparisons, quasi‑experimental methods, and uncertainty measurements to help overcome these constraints.

The ideal candidate possesses strong analytical judgment and practical product sense. Ambiguous business questions do not intimidate you. You have a keen sense for when additional data or analysis could materially change a conclusion, and when it wouldn’t. You apply analytical rigor while balancing what is functionally required to advance a project. Your aim is to drive better decisions and faster learning through measurable customer outcomes.

What You’ll Do

• Act as an embedded Data partner to Product, Design, and Engineering, helping shape strategy, product proposals, and experiments from the earliest stages.
• Build analytical frameworks across the full PLG journey from acquisition and activation through engagement, adoption, expansion, monetization, and durability
• Use funnel, cohort, journey, and sequence analysis to identify friction and opportunities for improvement.
• Identify the behaviors and milestones that predict conversion, production readiness, expansion, churn, and long‑term customer success, and translate them into leading indicators for successful or stalled accounts.
• Analyze feature discovery and adoption patterns to recommend interventions that increase successful adoption and expansion.
• Design and evaluate experiments and product changes, using matched comparisons, pre/post‑intervention analysis, causal methods, and other appropriate techniques when conventional A/B testing is not practical.
• Clearly distinguish observed results from assumptions, quantify uncertainty, and explain the confidence behind each conclusion.
• Help prioritize growth opportunities based on potential impact, confidence, effort, and measurement feasibility.
• Build reusable datasets, metrics, dashboards, and analytical tools that reduce ad hoc work and make insights accessible to Product, Marketing, Sales, and leadership.
• Partner with Engineering and Data Engineering to improve event instrumentation, data quality, and the analytical models required for reliable product analysis.
• Communicate findings through clear visualizations, written narratives, and practical recommendations for technical and non‑technical audiences.

What You’ll Focus on First

During your first several months, you will help the team: - Audit signals currently captured in the onboarding flow and recommend new instrumentation as needed - Establish reporting and repeatable analysis for PLG experiments. - Analyze user behavior after the first successful Activity or Workflow. - Identify signals of production readiness and common points where users stall. - Map feature‑adoption paths across important product areas.

What You’ll Bring

• A strong foundation in statistics, experimental design, causal reasoning, and quantitative analysis.
• Experience using product, behavioral, or event data to improve activation, engagement, retention, conversion, or expansion.
• Experience working with small samples, noisy signals, imperfect control groups, or environments where standard A/B testing is not always possible.
• Strong judgment in choosing methods that fit the decision, available data, and level of uncertainty.
• Proficiency in SQL and Python for analysis, modeling, and automation.
• Experience with cohort analysis, funnel analysis, segmentation, predictive modeling, and supervised or unsupervised machine‑learning methods.
• Ability to prototype quickly in notebooks and convert recurring analyses into reliable data products, models, or workflows.
• Experience with modern data platforms and query engines such as Athena, Presto/Trino, BigQuery, or Snowflake.
• Familiarity with cloud and object‑store technologies such as AWS S3.
• Experience building dashboards and reusable analytical assets in a modern business intelligence platform.
• Comfort working with evolving definitions, incomplete instrumentation, and trade‑offs between analytical precision and decision usefulness.
• A results‑oriented mindset and a record of translating analysis into product or business action.
• Strong communication skills, including the ability to explain methods, uncertainty, and recommendations in plain language.
• Curiosity about developer platforms, cloud infrastructure, usage‑based products, and how customers adopt technically complex products.
• A collaborative approach and the ability work effectively with Product, Engineering, Marketing, Sales, Finance, and Data partners.

Compensation

• Tier 1: $172K – $220K • Offers Equity
• Tier 2: $154K – $195K • Offers Equity
• Tier 3: $137K – $175K • Offers Equity

Compensation ranges reflect salary across several geographic markets. Employment offers carefully consider multiple factors, including prior experience, knowledge, expertise, skillset, market location, and job level assessed during the interview process.

Apply: Senior Data Scientist at Temporal Technologies

I have been searching for a fulltime job since May and I haven't been able to get more than 3 interviews. The market is not doing well, we all know that but the calamity inspired me to earn from other ways. These last few months I was working on skilling up and becoming more employable, I kept coming across videos of Agentic AI and product engineering and something struck me. I had created a project to showcase my data science skills and now I am turning it into a sellable product but via vibe coding since I am not a SD.

I see this as a silver lining, share something of your own?

Company - Deepdimex

Role - AI & Data Science Intern

Batch - 2026/2027/2028

Stipend - ₹20,000/month

Location - Remote

Requirements

- Strong analytical and problem-solving skills.

- Basic knowledge of statistics, data science, and machine learning.

- Familiarity with Python or R, Pandas, NumPy, and SQL.

- Understanding of data analysis, visualization, and reporting.

- Good communication and teamwork skills.

How to Apply

Email: garima.bhat@deepdimex.com

Note: Share your CV by email or Whatsapp. No calls, please.

Hey! I'm currently doing a data science master degree after my data engineering bachelor.

I had some work experience while doing my bachelor thesis in a research lab in Japan! It was really interesting, I was allowed to progress at my own pace etc, being quite autonomous.

My question is the following: How is the data scientist job changing now in this agentic era? I personally dislike using agentic workflow because it kills the fun I have and it gets boring.

What about medical data science?

I’m graduating in December 2026 with a BA in Economics from UMass Amherst and starting Georgia Tech’s Online MS in Analytics (OMSA) in January 2027, with plans to pursue the Computational Data Analytics track.
I’ve been trying to transition toward data science and I’m wondering whether my current experience makes me a credible candidate for entry-level Data Scientist positions or whether I should focus on Data Analyst and Research Analyst roles while developing my technical skills.

My background:

Education: BA in Economics, approximately 3.5 GPA. Incoming Georgia Tech OMSA student.

Current internship: Audience Research Consulting Intern at a research firm in Washington, DC. I work with survey data, statistical analysis, data visualization, and research reporting. I’ve also worked with ordinal regression models.

Research experience: Previously worked as an undergraduate economics research assistant. I’ve also completed an independent electricity market research project analyzing wholesale electricity prices, renewable generation, and other economic variables using regression analysis.

Programming: R is my strongest language. I’m comfortable with statistical analysis, regression modeling, and data manipulation. I’ve recently been developing my Python skills, particularly pandas, NumPy, and visualization libraries. I’m also learning SQL.

Statistics: Undergraduate econometrics, regression analysis, hypothesis testing, and applied economic research. Currently independently studying causal inference and machine learning.

Projects: Electricity market econometric analysis, survey research, and other quantitative research projects.

What I’m concerned about:
Although I have experience working with real data and statistical models, most of my work has been in R and applied economic research rather than traditional data science or machine learning.
My Python and SQL skills are still developing, and I haven’t yet completed a substantial end-to-end machine learning project.

My questions:
Based on my background and resume, am I competitive for entry-level Data Scientist roles?
What are the biggest gaps in my resume that would prevent me from getting interviews?
Would I be better off applying primarily to Data Analyst, Research Analyst, or Product Analyst positions for now?
how would you evaluate my current experience compared with other entry-level applicants?

I’m interested in eventually working in data science, particularly in fintech, energy, or economic research.
I’d appreciate candid feedback, especially from people involved in hiring. I’m trying to figure out whether I’m ready to start applying seriously or whether I need another 6 to 12 months of preparation.

Hey everyone!
I’m a Data Scientist with over 3 years of experience, and I'm currently preparing to make a move to a FAANG+ company to push my learning further and it better aligns with my growth goals and personal commitments.
I have 3+ years of professional experience as a Data Scientist working on end-to-end projects, but I want to structure my preparation more rigorously to crack top tier interviews. I want to bridge any gaps in my knowledge and prep :)
I’d love some guidance from those who have been through this process:
- What core technical skills, system design concepts, and advanced topics FAANG+ companies currently expect from a Data Scientist with 3+ years of experience?
- Where should I start my preparation?
- What specific competencies (coding, ML system design, stats/product sense) do they look for?
- What resources or roadmaps worked best for you?

Any advice, tips, or mentorship would be greatly appreciated.
Thank you

I work at Wissen Technology (Wissen Infotech) and can refer candidates for our current India openings — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Current openings:

• Database Engineer – TEDRA | Mumbai | 5-7 yrs | Python, Sybase, Hadoop
• AI Implementation Engineer | Bengaluru | 6-12 yrs | Spring, Python, React
• Python AI Engineer | Bengaluru | 5-8 yrs | Python, Pandas, CI/CD
• AI Control Plane - FullStack | Hyderabad | 3-6 yrs | Python, Django, Flask
• AI/ML Engineer | Bengaluru | 2-5 yrs | Python, NLP, LLM

Full list: https://careers.wissen.com/jobs/Careers — if your role isn't above, mention it in the DM.

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches a role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.

I'm a BBA(Business analytics) student. I have done some ML projects and am still working on a different one

How hard/easy it is going to be for me land my first internship ?

​Hey everyone,

​I’m an undergrad Data Science major (graduating Fall 2027) and I’ve applied to 20+ Data Science and ML internships recently. Every single one has come back as a rejection email within 3 days of applying.

​I already have a previous data science internship (Python, SQL, R), math tutoring experience, a hackathon award, and ML projects on my resume, so getting rejected that fast every time doesn't make sense to me.

​Why am I getting rejected within 72 hours, and what should I do next? Should I tweak my resume and re-apply to the same roles, or take a completely different approach?

I made a list of FRESH Data Science jobs. All these have opened just recently, so there is still chance to apply. I hope this helps someone!

• Scientist, Discovery Cheminformatics @ Octant Bio

  • 💰 $145–185K/y

• Staff Machine Learning Engineer @ ServiceNow

  • 💰 $176–308K/y

• Staff Machine Learning Engineer, Ads Conversion Core Modeling @ Pinterest

  • 💰 $223–390K/y

• Director, Commercial Data Strategy @ Olema Oncology

  • 💰 $220–240K/y

• Machine Learning Engineer @ Accenture Federal Services

  • 💰 $108–203K/y

• Sr. Specialist, Decision Intelligence (m/f/d) @ MSD Ireland (Ballydine)

  • 💰 $117–184K/y

• Sr AI Data Science Manager @ KeyBank National Association

  • 💰 $116–216K/y

• AI Research Scientist, Agentic Systems (Remote) @ CrowdStrike Mexico S. de R.L. de C.V.

  • 💰 $120–180K/y

• 2027 Spring Co op Biologics Design and AI Cambridge MA @ () Opella Healthcare IN P.Ltd

  • 💰 $47 – $60/h

• Senior Data Scientist @ AbbVie

  • 💰 $110–209K/y

• Finance AI Analyst @ Intuitive

• Data Scientist, Intern @ Duolingo

  • 💰 $54 – $56/h

• Senior Data Scientist @ Cint

  • 💰 $115–165K/y

• Senior Manager, Statistical Programming @ IMVT Corporation

  • 💰 $175–195K/y

• Sr. Machine Learning Engineer @ PitchBook Data

• Principal Data Science @ Fidelity Management & Research (Hong Kong) Limited

  • 💰 $126–255K/y

• Staff Data Scientist @ TransUnion

  • 💰 $113–188K/y

• Data Scientist SME @ LEIDOS INNOVATIONS UK LTD.

  • 💰 $131–237K/y

• AI/ML for Biology Scientist @ U (FCRS = US014) Novartis Pharmaceuticals Corporation

  • 💰 $126–234K/y

• Human Performance Data Scientist @ Booz Allen Hamilton_United States

  • 💰 $87–198K/y

• Sr. Machine Learning Engineer @ Canada Workday ULC

• Artificial Intelligence / Machine Learning Engineer @ FIS Global Business Solutions India Private Ltd

• Senior Machine Learning Research Scientist @ G Pfizer Healthcare India Private Limited

• Senior Data Scientist - Intelligence Support (TS/SCI) @ Xcellent Technology Solutions

  • 💰 $110–118K/y

• Data Science Analyst @ Concord USA

  • 💰 $75–85K/y

• CD&A Data Scientist, Obesity - Senior Associate @ Amgen Technology (Ireland) UC

  • 💰 $104–141K/y

• Reinforcement Learning Engineer @ Bright Vision Technologies

  • 💰 $100–150K/y

Thanks for reading! If you want another batch of Data Science jobs, just say so in the comments.

Looking at remote worldwide for the past 7 days - Brazil, United States, Colombia, and others

Here are the jobs I found, organized by level:

Entry Level:

• Associate Data Scientist @ Capgemini (Brazil)
• Data Scientist @ Significance (United States) - $115K - $125K
• Data Scientist @ ICF (United States) - $81K - $139K
• Data Scientist @ Applaudo (Colombia)
• Consultor Data Science @ Capgemini (Spain)
• Data Scientist @ Atos (United Kingdom)
• AI Data Scientist @ Koniag Government Services (United States)
• Media & Marketing Data Scientist @ Go Fish (United States)

Senior:

• Senior Data Scientist @ Coinbase (United States) - $180K - $212K
• Senior Data Scientist @ Cint (United States) - $115K - $165K
• Senior Data Scientist @ Sitetracker (United States) - $145K - $215K
• Senior Data Scientist – Supply Chain @ US Foods (United States) - $100K - $155K
• Senior Data Scientist – Delivery Tech @ Gopuff (United States) - $160K - $200K
• Senior Data Scientist @ Imagine Pediatrics (United States) - $145K - $180K
• Senior Data Scientist II – Product Analytics @ Smartsheet (United States) - $155K - $185K
• Senior Data Scientist @ Takeaway.com (Canada)
• Senior Applied Data Scientist @ Belvo (Mexico)
• Senior Applied Data Scientist @ Applaudo (Peru)
• Senior Consultant, Data Science – Analytics @ TransUnion (Costa Rica)

Manager:

• Applied Data Scientist – Performance Management, AI Solutions @ Leidos (United States) - $87K - $157K
• Principal Data Scientist @ Spokeo (United States) - $166K - $216K
• Staff Data Scientist @ Reddit, Inc. (Canada)
• Global Supply Planning Data Science Manager @ Mondelēz International (India)

Quick notes: * All of these are fully remote (location requirements vary by role) * Apply directly on company sites

Hope this helps someone!

For a research project in the cultural sphere, we’re looking for someone to help us scrape unstructured data from across the web, clean it, integrate it with our own data sources, and ultimately connect everything into one reliable dataset. On top of that dataset, you’ll build a multimodal embedding space to uncover relationships and patterns within the data.

Experience with web scraping, data pipelines, data engineering and multimodal embeddings is essential, and you should be comfortable working with agentic coding tools. We’re not looking for any specific academic background, but for someone savvy, resourceful and quick who has done this kind of work before.

DM me with a little bit about you. :)

Hello, everybody. I read a lot of people's issues with the interview for Ethos when it comes to getting matched to the role that actually fits your domain. Many people applying through the general interview intended to match them with a project or role in their domain end up matched with something unrelated to their field. In my case, I was matched with roles that not only have nothing to do with my domain but also that I am definitely not qualified for. I therefore decided to make a megalist so you can apply directly instead of wasting your time, like me, hoping to get matched with the right role. Hope this helps!:

Technology, Data & Engineering:

Cybersecurity / IT GRC Specialist — $90/hr
Engineering / Manufacturing & Technical Ops — $90/hr
Business Intelligence/Data Analyst — $80/hr
Incident Management / SRE & Reliability Lead — $80/hr
Product Manager — $80/hr
Product Manager (Tech) — $80/hr
Sales Engineer / Solutions Consultant — $80/hr
Software / AI / IT & Data Generalist — $80/hr

Finance, Accounting & Investing:

Corporate Development / M&A Manager — $100/hr
Equity Research Analyst — $100/hr
Financial Analyst — $100/hr
Financial Services Compliance / AI Regulatory — $100/hr
FP&A / Corporate Finance Analyst — $100/hr
Hedge Fund / Asset Management Analyst — $100/hr
Investment Analyst / Valuation & Credit Specialist — $100/hr
Investment Banking Analyst — $100/hr
Investment Banking Analyst / Associate — $100/hr
Investment Banking VP / Director — $100/hr
Investor & Fundraising Specialist — $100/hr
Investor Relations Associate — $100/hr
Investor Relations Manager — $100/hr
M&A Analyst — $100/hr
M&A Associate — $100/hr
Private Equity Associate / VP — $100/hr
Restructuring & Turnaround Advisor — $100/hr
Transaction Services / Financial Due Diligence Professional — $100/hr
Venture Capital Associate / Principal — $100/hr
Pricing Strategist / Revenue Economics Analyst — $90/hr
Accountant / Finance Operations & Audit Support — $80/hr
Auditor (CPA) — $80/hr
FP&A Manager / Director — $80/hr
Tax Professional — $80/hr
Personal Finance / Consumer Planning Advisor — $70/hr
Senior Financial Analyst (FP&A) — $70/hr

Healthcare & Life Sciences:

Clinical & Biomedical Specialist / Pharma Consultant — $100/hr
Healthcare Operations Consultant — $100/hr
Healthcare Strategy Consultant — $100/hr
Medical Science Liaison / Medical Affairs Professional — $100/hr
Biologist / Environmental Scientist — $90/hr
Public Health Communications Specialist — $90/hr
Pharmaceutical Brand / Commercial Manager — $80/hr

Legal, Compliance & Public Sector:

Contracts Attorney / Legal Diligence & Redlines — $100/hr
IP Counsel / Trademark & Copyright Attorney — $100/hr
Legal, Privacy & Regulatory Compliance Analyst — $90/hr
Risk & Regulatory Advisory Consultant — $80/hr
Government / Public Administration Professional — $70/hr
Policy Researcher / Think Tank Analyst — $70/hr

Education, Research & Creative Work:

Japanese Language & Cultural Fluency Consultant — $100/hr
Special Education Specialist / IEP Consultant — $90/hr
Brand / Creative Direction & Marketing Collateral — $80/hr
Creative Director / Art Director — $80/hr
Educator / School Professional — $80/hr
University Professor / Lecturer — $80/hr
Document, Deck & Spreadsheet QA Specialist — $70/hr
Humanities / Arts / Culture Professional — $70/hr
Nonprofit / Philanthropy / Community Programs — $70/hr
Presentation Specialist / Visual Graphics Designer (Consulting) — $70/hr

Sales, Marketing & Customer Experience:

Training / Onboarding / L&D Specialist — $70/hr
Account Executive — $100/hr
GTM Manager — $100/hr
Partnerships Manager (BD) — $100/hr
Product Marketing Manager — $100/hr
Revenue/GTM Operations Specialist — $100/hr
Sales / GTM Strategist — $100/hr
Sales Manager — $100/hr
Senior Account Executive — $100/hr
Enterprise Account Executive (B2B) — $80/hr
Agency Account Director — $70/hr
Brand Strategist / Brand Manager — $70/hr
Corporate Communications Manager — $70/hr
Customer Success / Support Operations Lead — $70/hr
Customer Success Manager (Enterprise) — $70/hr
Executive Communications Manager / Speechwriter — $70/hr
Market Research / Competitive Intelligence Analyst — $70/hr
Market Research & Consumer Insights Manager — $70/hr
Marketing Manager (B2B) — $70/hr
Media / Journalism / Communications Professional — $70/hr
Proposal Manager / Bid Writer — $70/hr
Sales Enablement Manager — $70/hr

Consulting, Strategy & Operations:

Business Development Manager — $100/hr
Consulting Engagement Manager / Project Leader — $100/hr
Management Consultant — $100/hr
Market Access / HEOR Specialist — $100/hr
Public-Sector Procurement / RFP Response Lead — $100/hr
Chief of Staff / Business Operations Lead — $80/hr
Corporate Strategy Manager — $80/hr
Economic Consultant — $80/hr
Independent Strategy & Presentation Consultant — $80/hr
Management Consultant (Advisory & Transformation) — $80/hr
Startup Pitch Deck & Fundraising Specialist — $80/hr
Strategy Consultant — $80/hr
Operations Manager / Capacity & Process Improvement — $70/hr
People Ops / Recruiting Generalist — $70/hr
Procurement / Vendor Management Lead — $70/hr
Program Manager / PMO Lead — $70/hr
Program Manager / PMO Lead — $70/hr
Real Estate / Hospitality / Events Professional — $70/hr

Disclaimer: The links provided are referral links.

Hi everyone,

I’m currently working in a different domain and want to switch my domain. I’ve completed a Data Science course and learned SQL, Python, Pandas, MySQL, Power BI and data visualization.

I want to gain hands-on experience working on real-world data projects to build my portfolio and improve my practical skills.

Could you please suggest websites, companies, startups, or communities where I can find remote internships or project-based opportunities, preferably suitable for career switchers?

If they offer genuine learning opportunities and meaningful project experience.

Any suggestions or personal experiences would be greatly appreciated. Thank you!

I created a startup earlier this year that is aiming to create a zero-code machine learning application. I currently have an MVP and am looking for someone to build upon it. I have limited knowledge of machine learning from college and am looking for someone who is an expert in supervised machine learning models. This person will also have to be a master of Python since the current product is built in Python. Any other knowledge and experience in other programming languages is a plus. Can be located anywhere in the U.S., but Boston would be optimal. If interested, let me know!

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit.

In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit's Ads marketplace. You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale. You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long‑term vision for measurement, prediction, and optimization.

As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team. If you are passionate about applying foundational quantitative science to solve complex, high‑impact business problems, join us in shaping the future of Reddit ads.

What you’ll do

• Define the future of Ads Data Science: Own the design and long‑term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance.
• Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full‑funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue.
• Drive end‑to‑end impact: Take end‑to‑end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments.
• Establish scientific standards: Define and codify best practices for large‑scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams.
• Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large‑scale behavioral data, foundational models for strategic insights, and the economics of marketplace dynamics.
• Translate ambiguity into outcomes: Influence the design and definition of core business and performance metrics, robust measurement methodologies, and collaborate deeply with cross‑org XFNs to align on strategic goals and translate insights into tangible action.
• Influence and uplevel the organization: Lead technically minded peers and mentor senior data scientists, influencing technical and statistical direction across the entire product and engineering organization, and championing innovation in ad systems through advanced quantitative techniques.

Requirements

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
• Master's or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
• For M.S. holders: 12+ years of industry experience in applied science, data science, or machine learning engineering roles
• For Ph.D. holders: 8+ years of relevant experience applied science, data science, or machine learning engineering roles
• Advanced proficiency in statistical programming (Python or R) and SQL
• Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques
• Strong understanding of experimental design, causal inference, or A/B testing methodologies
• Exceptional problem‑solving and communication skills, with a track record of influencing product and engineering partners
• Experience working in fast‑paced, ambiguous environments with cross‑functional teams
• Proven experience in influencing large (500+ engineers/data scientists) organizations on technical direction, statistical rigor, and machine learning best practice

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender‑Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency:

The base salary range for this position is: $268,000 — $365,100 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment‑Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to the Candidate Privacy Policy for Potential Employees and Contractors.

Apply: Principal Data Scientist, Ads at Reddit

Hi everyone! 👋
I’m an AI & Data Science student currently looking for opportunities to gain real-world experience.
I’m open to:
💼 Internships — Python / Backend / AI-ML / Data Science
💻 Freelance projects
🚀 Student/startup projects
🤝 Open-source collaborations
🧠 AI/RAG/Chatbot projects
**Skills I work with:**
Python, FastAPI, Flask
SQL, MongoDB
React, Vite, Tailwind CSS
REST APIs & backend development
Machine Learning & Data Science
RAG systems, embeddings & vector databases
Git/GitHub
Ollama & local LLMs
I’ve worked on projects involving **RAG-based PDF Q&A systems, Telegram AI bots, business analytics, college discovery platforms, and full-stack applications.**
I’m mainly looking for opportunities where I can **build something useful, learn from experienced developers, and contribute to a real project.**
If you have an internship, freelance project, startup idea, or collaboration opportunity, feel free to **DM me**. I can share my GitHub, portfolio, resume, and project demos.
Thanks! 🙌

A friend of mine has been looking for a data science job over 2 years now. She took a break after having a baby . She has worked aa python developer and a data scientist at a wireless company. Would appreciate any leads or advice.

Hi!!
I’m a data science intern applying and I know there’s going to be a case study and you have to explain it! I heard there’s a coding assessment down the line as well and I just wanted to see if anyone has any experience with red ventures interview process or advice on what to review or nail before the coding assessment! All advice is appreciated so much!!!

Hi All!

I did my MS in Electrical and Computer Engg from Georgia Tech in the US, and joined a big semiconductor company in late 2021. My work involves building production grade ML models for designing the photomasks used for lithography process used in chip manufacturing process. What I do on a daily basis, is done by probably few hundred people in the world.

I have worked at the frontiers of Physics, Data Science, and Machine Learning during this time, and I bring a mature understanding to the table in understanding the nuances of the problems and developing optimal solutions. More importantly, I have been told that I’m a quick learner and a person with high emotional intelligence.

I moved to India sometime ago, and have been working with the same US team from India. I’m now looking to move to a different company in India, and am looking for Data Scientist/ML Engineer/AI engineer roles.

This would be my first switch since my current job was the first after my University education. How should I go about my job search? Is LinkedIn job posts still the best way to go about it? I’m open to any suggestions/recommendations/opportunities.

Hey everyone, I wanted to ask how applicable knowing R is in the private sector over there in the US.

I’m graduating with a degree in Social Sciences in Brazil. Down here, knowing R is pretty limited unless you're working for the government, academia, or a few specific research institutes.

How does it work over there? Are private companies actually hiring people with social science backgrounds who know R, or is it heavily dominated by Python/SQL

I was thinking of joining a professional data science organization to like network and maybe learn why I'm having such a hard time getting any leads. Does anyone have experience with professional orgs? Also is there one I should definitely join or avoid? Thanks in advance for any insights!

Has any one attended Optum: From Possible to Practical Bangalore at Kalyani Magnum office today, how was it, is it good for job seekers to attend or what is it all about?