Machine Learning Scientist Jobs

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best Data Intelligence Platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products. The impact you will have: Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights. Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations a

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Lead Director, Lead Director - Data Scientist - Forecasting Accuracy and Analytical insights for Underwriting , ensures the accuracy, reliability, and financial integrity of analytics-driven products across the underwriting ecosystem. This leader sets the strategy for reducing financial leakage, goal-seeking underwriting scenario optimization, forecasted P&L accuracy, underwriting risk-management, insights and recommendations for underwriting/sales decision making, and anomaly detection in live underwriting deals. They ensure that underwriters and sales partners are supported by technology with various financial tools, data, and insights. This role combines the analytical rigor of a Data Scientist with the leadership capabilities of a financial product development leader. The position leads a team of 10+ data scientists responsible for supporting underwriting analytical needs, P&L forecasting accuracy, analytical insights and validation, reporting solutions, business impact, and financial result verification. Key Responsibilities: Product‑Embedded Leadership for Data Science & Advanced Analytics Lead the data science and analytics strategy for underwriting transformation software products, from problem framing through production deployment. Design and operationalize predictive, and scenario‑based analytical cap

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Overview CVS Health is seeking a Data Scientist to join its enterprise clinical intelligence platform team. AI is unlocking new possibilities in healthcare at an unprecedented pace, and that progress comes with a responsibility to build capabilities that are clinically rigorous, ethically grounded, and worthy of the trust patients and providers place in them. This role will analyze clinical data and develop AI and machine learning solutions that generate evidence-backed insights for use cases across CVS Health. The Data Scientist will work closely with experienced data scientists, engineers, product managers, and clinical partners to build, evaluate, and improve solutions used in production. What You’ll Do Develop subject matter expertise in clinical data and its application to healthcare problems. Explore, analyze, and summarize large structured and unstructured datasets to inform product and modeling decisions. <span

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in! At Duolingo, you’ll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. You’ll have limitless learning opportunities and daily collaborations with world-class minds — while doing work that’s both meaningful and fun. Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world. Read our blog to learn more. About the role You will... Derive insights from data to influence product roadmaps and drive business results Apply advanced analytical methods, structural approaches, causal inference, and/or machine learning and AI to model user behavior and estimate the impact of potential new feature implementations, and collaborate with product and engineering teams to develop solutions Evaluate product experiments to create and improve user experiences Communicate and present findings and recommendations to senior management Help preserve our culture of fact-based decision making as we scale You have... Pursuing a PhD degree (in at least the third year of PhD program) in a quantitative field (e.g. Economics, Finance, Statistics, Math, Linguistics, Computer Science, Computational Social Science, ML/AI), ideally planning to graduate in Fall 2027 or Spring/Summer 2028 Strong understanding of consumer digital products and an interest in applying advanced analytics and economics to business outcomes Previous experience analyzing large datasets, communicating results to technical and non-technical senior-level audiences, and making actionable recommendations that improve the product or business Skilled in SQL, R or Python, and/or statistical methods to analyze behavioral data Enthusiasm for learning and sharing analytical methods to h

Become a part of our caring community The Research Scientist 2 participates in research study design, analysis and interpretation of results, with special emphasis on statistical and analytical plan development; data acquisition, preparation, and management; statistical analysis and interpretation of findings. The Research Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. Humana’s Healthcare Quality & Reporting Improvement (HQRI) department is seeking a Research Scientist 2 to join a high-performing team dedicated to advancing predictive modeling and analytics in support of our Medicare and Medicaid business. The HQRI team plays a pivotal role within Humana, delivering insights that drive the effectiveness of risk adjustment initiatives. In this position, the Research Scientist 2 will partner with a senior research scientist to apply advanced statistical methods to rigorously evaluate the impact of risk adjustment programs and pilot projects. The findings generated will be critical in informing key business decisions and optimizing operational strategies. Additionally, the person in this role will collaborate with colleagues specializing in data science and actuarial analytics. We are seeking a candidate who brings complementary skills to the team, with the ability to learn from their teammates while contributing with their unique expertise in statistical analysis. Use your skills to make an impact Required Qualifications Bachelor's degree in Computer Science, Data Science, Mathematics or a related quantitative field; 2 years of experience applying statistical modeling, pred

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The opportunity: Flexport is looking for a creative, technically-minded Senior Data Scientist who is excited about solving challenging problems in fulfillment and logistics. We provide ecommerce merchants a full range of "factory to door" logistics solutions. This role focuses on building automated decision-making processes that ensure that we meet or exceed the expectations of our merchants for fulfillment speed and reliability, while growing the network in a cost-efficient way. Data is at the heart of our business, and as a Data Scientist, you will develop first-in-class science products to make fulfillment easy and efficient for our merchants. In collaboration with multidisciplinary product, engineering, and business/operations teams, you will apply advanced Operations Research (OR) and Machine Learning (ML) methods to deliver data-driven insights and automated decision-making solutions in Flexport’s fulfillment products. Our business, product, and engineering teams collaborate closely with our Data Scientists to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. We are passionate about prov

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Data Scientist on the Digital Experience Insights team, you'll lead high-impact analytics initiatives, turning complex data, platform, and time-series data into rigorous predictive models, causal inferences, and strategic product metrics. You'll also apply advanced statistical and quantitative research methods to some of our most complex datasets, but the core of the role is turning that analysis into decisions leadership can act on. This role sits within a fast-moving analytics organization where the specific problems shift over time, so we're looking for someone with strong research rigor who can adapt it to whatever question is in front of them. WHAT YOU'LL DO Advanced Predictive & Statistical Modeling: Develop ML models spanning predictive modeling, time-series prediction, clustering, churn reduction, anomaly detection, and recommendation systems. Quantitative Research: Apply advanced computational methods and statistical techniques, including multilevel models and Statsmodels, to massive datasets. Executive Visualization: Create executive-level visual analytics that make complex findings accessible to senior stakeholders. Stakeholder Collaboration: Partner directly with Product, Engineering, and Business leaders to translate complex analytical findings into actionable strategy. We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in complia

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Marketplace team at Lyft is responsible for accelerating the growth of the business while simultaneously delivering on key business and financial metrics, and Dynamic Pricing & Offer Selection is an integral part of that. Our team is the dynamic pricing team responsible for leveraging both real-time and historical data to set prices for every single ride at Lyft while balancing prices and ETAs to better serve our riders’ needs. We are looking for fast learning, data-driven individuals who are passionate about tackling these open-ended problems in pricing theory and making a large, positive impact in the business. In this role, you will work closely with Product and Engineering on a cross-functional team to prototype and build end-to-end dynamic pricing models that can operate at scale. In addition, you will be expected to leverage your domain knowledge and influence existing and future roadmaps to help Lyft continue to deliver a better experience for riders and drivers. Responsibilities: Partner with other scientists, colleagues in the pricing team, and with external teams to formalize problems mathematically and within the business context Perform complex data analysis to gain a deeper understanding of problems by identifying their root causes Develop and fit statistical, machine learning, or optimization models Write production code; collaborate with Software Engineers to ship models to production Design and implement both simulated and live experiments Analyze experimental and observational data; facilitate launch decisions Communicate findings to a broad audience consisting of Product, Engineering, and executive leadership Experience: Data Scientist with experience in Machine Learning, Statistics, Economics, or other quantitative fields M.S. or Ph.D. in Computer Science, Economics, Statis

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers. What You’ll Do Our Data Scientists are responsible for the entire model development lifecycle, from conception with stakeholders, through model development and productionization, to following through to see that the desired business impact is achieved — including circling back with stakeholders to make product or strategic decisions. Responsibilities Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience. Be responsible for the full machine learning

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including: How do we improve the quality of our map data in order to improve our recommendations? How do we benchmark and measure the success of our services? How do we validate features of the real world that affect our routing algorithms? Are we meeting our travel estimation promises to our customers? Responsibilities: Leverage data and analytic frameworks to identify opportunities for growth and efficiency Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals Design and analyze online experiments; communicate results and act on launch decisions Develop analytical frameworks to monitor business and product performance Establish metrics that measure the health of our products, as well as rider and driver experience Identify and drive impact and alignment, shaping product and business strategy

Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, offer buy now, pay later functionality, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale. Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same. The Role We are looking for a quantitative, AI-fluent early-career professional to fill a data science role focused on payments data across Square and Cash App. You will partner closely with Product, Operations, Finance, and Engineering, leveraging data tools to optimize our payments platform from success rate, to cost efficiency, to risk mitigation. In addition to vertical work focused on the Payments domain, we also expect you to contribute to horizontal initiatives across the broader Data Org from data systems, to process and tooling. You Will Leverage AI to create scalable data tools, agents, and automations Partner with Product, Engineering, Finance, and Operations teams to systemize and make data-driven deci

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist What is the opportunity? We are seeking a highly skilled and motivated Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains. What will you do? • Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards. • Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services. • Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions. • Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network. • Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions. • T

The Opportunity This is an exciting time at Enigma. We’re on the cusp of releasing our next generation of small business intelligence products built on years of learnings in the space. We are seeking an experienced Data Scientist to join our Entity Resolution team and help shape the trajectory of these products. Your work will directly impact the accuracy, scalability, and predictive capabilities of our data platform, influencing key business decisions for our customers. The Role Data is at the core of Enigma’s product, which makes data science the beating heart of what we ship. As a Data Scientist on the Entity Resolution Team, you will work in a cross-functional team alongside other data scientists, engineers, and business stakeholders. You will own problems end to end–from raw source data, through models and scalable pipelines, to the customer interface. Your impact will be measured by the contributions you make with your team to improve the accuracy of our data and the value of our product to our customers. What You’ll Do Translate customer goals into working solutions, using large-scale data transformation, sound statistics, and high-quality code. Most of our work is in Databricks (both Spark SQL + PySpark), supported by statistical tooling, and by ML/AI where the problem calls for it. Set a high standard for rigorous analysis and model development, grounded in sound statistical practice, so that results are high-quality and reproducible. Treat data as a reflection of the real world, and develop repeatable strategies for validating results against ground truth. Develop techniques to detect gaps in our data, find the source, and close them in a way that improves the product. Apply a data-focused, first-principles approach to problem solving. We value people who bias toward simple and elegant solutions, but who can implement state-of-the-art models and techniques when the problem requires it What Makes This Role Exciting? Technical challenge : Enigma