Data Science And Analytics Intern Jobs

P-1414 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 5+ years of experience working in a related system Optional: PhD in databases or distributed systems About Databricks

Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 5+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Data Science Manager at Micron Fab15, you will be responsible for the vision, development, and management of a high performing and technical analytics team. Optimize team performance by collaborating with internal and external stakeholders to provide data-driven solutions to complex strategic and tactical challenges. This is a highly collaborative role with operations, engineering, management, information technology, etc. Combine problem-solving, data-analysis, and technical skills to identify, quantify, and solve business problems. You will lead and participate in a team that is constantly challenging the boundaries of what is possible. You will develop and improve individual capability of current and future Micron data scientists. Establish and monitor team performance metrics to identify and implement continual improvement opportunities. You will lead your team to generate algorithms, create computer models, and test and validate models that are scalable for production. Your team will discover and present business relevant “stories” to business stakeholders using data visualization methods. You will develop expert-level knowledge of Micron and use this knowledge to deliver prescriptive, actionable solutions to stakeholders. Be responsible for conveying corporate business initiatives, providing direction thereof, and driving a clear understanding of line of sight to department and corporate strategic objectives within your team. Lead research in and keep up to date on the latest devel

P-188 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are

P-188 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are

P-97 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 5+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based o

P-1416 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 7+ years of experience working in a related system Optional: PhD in databases or distributed systems About Dat

P-1415 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 5+ years of experience working in a related system Optional: PhD in databases or distributed systems About Dat

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions.We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions.We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking an experienced Staff Data Scientist to join our Finance & Business Operations team. This is a hybrid data-science / applied-AI / product-engineering role inside Pinterest's CFO organization. It sits at the intersection of forecasting and finance analytics, internal tool-building, and AI adoption — and the person in it is expected to operate across all three. The core mandate is to make the CFO org's forecasting and planning work faster, be more rigorous, and more self-serve. In practice that has meant owning a forecasting product end to end (data pipeline through user-facing UI), partnering directly with Finance, BizOps, and Core/Monetization stakeholders to embed it in their workflows, and turning the company's emerging AI platform capabilities into tools that finance teams actually use day to day. This is a high-

About the Team DoorDash is looking for an experienced Data Engineer to join our growing Tax Data Mart team. This role will be a key contributor to the team and will be responsible for building and operating the data pipelines and infrastructure that power analytics and decision-making across the company. As DoorDash continues to grow its global footprint across multiple business lines, we are looking for a candidate with experience designing and maintaining scalable data systems. This person will support and grow our unique community via your blend of engineering, technology, and process improvement experience. About the Role You will be reporting to the Manager of Tax Data Mart, and play an integral role in DoorDash’s data function, owning the processes for ingesting, transforming, and controlling our data, ensuring accuracy, and making it available to analytics and business users. As a member of this team, you will lead the design, implementation, and operation of data pipelines and related processes to support the Company’s exponential growth. You’re excited about this opportunity because you will… Design, build, and maintain scalable, reliable data pipelines (ETL/ELT) that serve data across the company Develop and optimize data models and warehouse structures to support analytics and reporting Participate in new business initiatives and identify their impact on existing data system(s) and processes. Work closely with Analytics, Data Science, and business partners in the development and validation of new data sources. Identify and document business, functional and technical requirements to support new business initiatives and to enhance existing system functionality. Leverage AI & AI assisted tooling to build and automate recurring data tasks & pipelines. Monitor data quality, reliability, and observability, and resolve data-related issues for our internal business partners. Participate in defining the Company’s data tooling needs, including the maintenan

About Bluevine Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best. Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed. We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next? This is a hybrid role . At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline. Key Responsibilities: Generative AI Research: Explore and evaluate Large Language Models (LLMs) and emerging generative AI techniques to identify impactful applications in data science. Model Fine-Tuning & Adaptation: Design and execute experiments to fine-tune or customize foundational models using domain-specific and internal datasets. Applied Generative AI Solutions: Leverage generative AI to enhance traditional machine learning use cases such as risk modeling, fraud detection, and customer analytics. Prompt Engineering & Evaluation: Develop effective prompting strategies and build robust evaluation and benchma

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. Join the Payments Risk Management team as a Fraud Risk Intern based in New York. This team sits at the intersection of payments, product, and security, working to protect Coinbase customers from fraud across critical payment rails like ACH, card, and real-time payments. You'll work alongside risk professionals and product teams to strengthen fraud controls, surface actionable insights from transaction data, and help maintain a seamless user experience while keeping bad actors off the platform. What you'll do: Write SQL queries and build dashboards to detect anomalous behavior, analyze risk trends, and support ongoing monitoring of payment fraud signals Synthesize data findings into clear narratives and present recommendations to Payments Risk leadership Partner with Product, Data Science, and Engineering stakeholders to develop and pressure-test risk management strategies Evaluate existing rules and controls for effectiveness, flagging high false-positive rates and recommending improvements Collaborate with Customer Experience and Risk Analytics teams to implement learnings that improve the user journey without introducing incremental risk Document and improve operational processes and procedures for the risk team Required Skills and Experience: Currently pursuing a degree or certificate in a technology, finance, or an

Opportunity Overview: This is an excellent opportunity for an outstanding Lead Healthcare Analystto join a Series C digital health company. You will work closely with clinicians, program implementation, operation experts, informaticists, data scientists, and actuaries to support data-driven clinical programs. These programs are essential in improving a) payor/provider/patient collaboration, b) quality of care and patient outcomes, and c) healthcare utilization and spending efficiency. The work will be fast-paced and project-based, with evolving needs requiring adaptability, curiosity, and grace under pressure. What you’ll do: Cultivate a deep understanding of Cohere’s clinical content, UM products and clinical programs and use analytics to produce insights to drive program effectiveness and value for internal business partners and clients. Lead clinical analytics projects, collaborating with multi-disciplinary partners, to understand business needs, clinical nuances, formulate plans, build and maintain analytical and reporting solutions. Independently lead in-depth analyses and Identify optimization opportunities by applying statistical data mining, and predictive modeling methods on administrative and clinical health data. Track cost, utilization, and industry trends to inform stakeholders of product performance and provide data-driven insights around opportunities to optimize clinical value for patients, providers and payors. Collaborate with clinical, account management, data science, and engineering partners to refine Cohere’s product features and client support. Foster a collaborative and innovative culture, mentor junior analysts. Maintain meticulous documentation and present findings or recommendations to company leadership and internal stakeholders What you’ll need: Work experience: 7+ years of experience working in a big-data analytics role. 2+ years of hands-on project leadership experience in the healthcare industry. Collaboration: Experience