Data Scientist Resume Sample - ATS Template 2026

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability. Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability. Contribute to self-service forecasting tools and internal platforms , enabling teams across OpenAI to access and act on real-time predictions. Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches. Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks. Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making. You might thrive in this role if you have: Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research). 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems. Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability. Proficiency in Python , SQL , and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries. Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments. Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders. Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1. Bonus if you have: Experience building or scaling forecasting platforms in a high-growth company. Familiarity with causal inference, Bayesian forecasting Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments. #LI-NM2 About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Posted 5 days ago

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro. We’re looking for an Applied Data Scientist who expects more from their career. It’s a chance to apply your expertise to distil complex problems into compelling insights using the best of machine learning and human creativity to deliver effective and impactful solutions for clients. Joining our advanced data science team, you’ll investigate, develop, implement and deploy a range of complex applications and components while working alongside super-smart colleagues challenging and rewriting the rules, not just following them. What we expect from you Degree in Statistics, Maths, Physics, Economics or similar field 2 to 4 years of experience required Programming skills (Python, ML, SQL are a must have) Analytical Techniques and Technology Logical thinking and problem solving Strong communication skills Experience with and passion for connecting your work directly to the customer experience, making a real and tangible impact Statistical Modelling and experience of applying data science into client problems. What you can expect from us We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn. And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. Our approach to Flexible Working At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

Posted 1 week ago

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We're hiring a hands-on Senior Applied Data Scientist to help build and scale production-grade recommendation systems that drive our core marketplace outcomes. This is not a research-only role . We're looking for someone who can take models from idea to production — running experiments, measuring business impact, and continuously improving the systems behind how Nift matches people with the right brands. You'll own the full lifecycle: exploratory analysis, data prep, modeling, testing, deployment, and post-launch measurement. The ideal candidate has worked in a real production environment, brings strong deep learning experience, and understands recommendation systems in practice — not just in theory. Success here means shipping models that move Nift's core KPIs, connecting technical work to measurable business impact, and helping the team scale with strong engineering discipline. This role is ideally based in Israel, but strong candidates in the U.S. will also be considered. What You'll Do Own the full funnel of applied machine learning work, from idea through production Build, improve, and deploy recommendation models that support Nift's core business goals Tackle deep learning problems in a production setting — not just offline experimentation Conduct exploratory data analysis, preprocessing, feature development, and modeling Run experiments and evaluate success against business KPIs, not just model metrics Partner with engineering and infrastructure teammates to productionize models and scale systems Improve recommendation quality, personalization, and the business performance tied to those systems What You'll Have 5+ years of experience in production data science environments Strong hands-on experience taking machine learning models into production Strong deep learning experience; proficiency with PyTorch or TensorFlow is expected Direct experience with recommendation systems, or adjacent experience in areas like bidding or dynamic pricing Strong Python and SQL skills Experience working with data at meaningful scale — high-scale environments are a strong plus The ability to measure model success through business outcomes such as revenue, conversion, churn, or similar KPIs Bonus points for: A Master's degree, especially paired with strong production experience A PhD paired with meaningful production-grade work (purely academic backgrounds aren't the target profile for this role) A software engineering background — particularly for candidates who've built pipelines and production systems before moving into machine learning About Us Our mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years . Now we're scaling to become one of the largest sources of new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we're poised for exponential growth and ready to demonstrate impact on a global scale.

Posted 2 weeks ago