Data Science And Analytics Intern Jobs

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Global Value Engineering Center of Excellence Become an integral part of our international, diverse, and dynamic Global Value Engineering Center of Excellence. Our Value Engineers are trusted advisors who operate at the intersection of technology and business , partnering with sales and customers to develop compelling Celonis-powered solutions and prototypes that address critical business challenges. We foster a fast-paced, collaborative environment built on trust, continuous learning, and mutual growth through coaching and mentorship. The Role: Launch Your Enterprise Software Career Kickstart your career in enterprise software through our immersive 12-month Orbit Program . This program offers a unique blend of client engagements, dedicated mentorship, and a strong team culture where collaboration and shared success are paramount. You'll leverage your technical background to develop essential Value Engineering skills, build lasting client relationships, and establish yourself as a trusted advisor, paving the way for significant career growth within Celonis. The Orbit Program is structured into classes and cohorts , with start dates organized twice a year. You'll likely join a cohort with a summer start date (June/July) or

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Global Value Engineering Center of Excellence Become an integral part of our international, diverse, and dynamic Global Value Engineering Center of Excellence. Our Value Engineers are trusted advisors who operate at the intersection of technology and business , partnering with sales and customers to develop compelling Celonis-powered solutions and prototypes that address critical business challenges. We foster a fast-paced, collaborative environment built on trust, continuous learning, and mutual growth through coaching and mentorship. The Role: Launch Your Enterprise Software Career Kickstart your career in enterprise software through our immersive 12-month Orbit Program . This program offers a unique blend of client engagements, dedicated mentorship, and a strong team culture where collaboration and shared success are paramount. You'll leverage your technical background to develop essential Value Engineering skills, build lasting client relationships, and establish yourself as a trusted advisor, paving the way for significant career growth within Celonis. The Orbit Program is structured into classes and cohorts , with start dates organized twice a year. You'll likely join a cohort with a summer start date (June/July) or

About the Team The Analytics team is looking for Data Analysts and Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our logistics platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. It is NOT just about building Machine Learning models and putting them into production. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Be a first-class thought partner to our product, business, finance and executive teams and help them make decisions on what’s next for DoorDash Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, R, or other scripting and statistical tools Produce recommendations and use statistical techniques and hypothesis testing and other experimentation techniques to validate your findings Provide insights to enable our cross-functional team to understand marketplace dynamics, user behaviours, and long-term t

Perplexity is AI for people who expect more. On the data team, that means building the systems that make our data reliable, understandable, and usable by both humans and AI. We're looking for an analytics engineer or data engineer who wants to build the foundation for an AI-native data organization. You'll design core data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that power the entire company: helping teams make strategic decisions, operate the business, and move faster with trusted data. You'll also make sure those systems are secure, privacy-aware, and legible to AI agents, data scientists, and the rest of the company. This role is for someone who can operate at the boundary of analytics engineering, data engineering, data governance, and internal product. You care about dimensional modeling, dbt standards, cost-aware warehouse design, access controls, privacy, and the details that make data trustworthy. You also believe AI should make the data stack faster, easier to maintain, and more accessible across the company without weakening security or governance. What You'll Do Build the core data foundation - design and maintain high-quality data models, marts, and pipelines that make analysis fast, reliable, and reusable. Manage the data warehouse - help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene so the platform scales cleanly. Make the warehouse AI-readable - own the documentation, semantic context, metadata, lineage, and retrieval patterns that AI systems depend on to understand and query Perplexity's data correctly. Own data modeling standards - define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes. Lead data governance practices - define standards for access, ownership, lineage, documentation, retention, quality, and sensitive data handling across the analytical warehouse.

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, causal inference, economics, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive toolbelt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. Teams Hiring for this role: Foundation AI: Our AI evaluation team focuses on generating high-quality models and consistently improving our evaluation models. Safety: Managing account relationships and the real-time morphing of linguistic mapping. Economy: Drive creator success and growth by exploring marketplace structure and pricing. Engine: This team is dedicated to enhancing Roblox's overall stability and performance, enabling all its functionalities. Social: Analyze user engagement to identify areas for enhancing the user experience and delivering greate

Data Platform & Analytics Manager – Millennium Space Systems Company: Millennium Space Systems Millennium Space Systems, a part of Boeing Defense, Space and Security (BDS), is a fast, agile small satellite company focused on national security space. Our missions have direct impact to global security, like missile warning and Earth observation. Our team is curious, bold and innovative. We take risks, innovate and explore new techniques and technologies. We influence change because we challenge the status quo. And when we watch our satellites launch, we know each one of us made it happen. Job Summary: The Data Platform & Analytics Manager is responsible for managing a team of experienced data engineers, scientists, and analysts. Develops and executes project and process plans, implements policies and procedures and sets operational goals. Acquiring resources for projects and processes provides technical management of suppliers and leads process improvements. Develops and maintains relationships and partnerships with customers, stakeholders, peers, partners and direct reports. Provides vision, oversight, and approval of technical approaches, products and processes. Manages, develops and motivates employees. This is an onsite role in our office in El Segundo, CA. This position’s internal job code is Data Science & Analytics Manager. Our team is currently hiring for a level K. Position Responsibilities: Team Leadership - Recruit, coach, and retain a high-performing team of data platform architects, data scientists, analytics/ML engineers, and BI analysts Enterprise Data Platform Ownership - Serve as technical authority for the data platform systems Process & Del

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows. AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations. The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production. This is a high-ownership role for someone who thrives in ambiguity, is e

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We operate at the intersection of Product, Engineering, Risk, Finance, and Go-to-Market to ensure that paying for OpenAI products is seamless, reliable, scalable, and globally optimized. As OpenAI expands internationally and across product surfaces, FinEng plays a critical role in enabling durable, efficient revenue growth. About the Role As a Data Scientist for Financial Engineering, you will drive the measurement, experimentation, and optimization work that powers OpenAI’s monetization infrastructure. You will define how we measure and improve checkout, payments, subscriptions, and pricing systems globally—balancing conversion, risk, cost, reliability, and user experience. As a senior individual contributor, you will establish source-of-truth metrics, design rigorous experiments, develop analytical frameworks, and translate complex findings into decisions that directly affect revenue and international growth. This role is based in San Francisco, CA. We use a hybrid model of three days per week in the office and offer relocation support. In this role, you will Define key metrics and guardrails across checkout, payments, subscriptions, and pricing. Design experiments, staged rollouts, and offline incrementality studies. Improve conversion, payment performance, retention, and involuntary churn. Develop pricing, elasticity, FX, and localization frameworks. Partner with Data Engineering to build trusted datasets and operational monitoring. Turn complex analysis into recommendations that shape product and business decisions. Provide technical leadership and mentor other data scientists. You might thrive in this role if you have 10+ years of experience in data science, experimentation, or product analytics. Experience with monetization, payments, checkout, subscr

Perplexity is AI for people who expect more. This role brings that same standard to how our data team works, with AI at the center of everything we do. We're looking for someone who's been a great data scientist, analytics engineer, or data engineer: the kind of person who knows which metric actually matters, can design an A/B test that answers the real question, has gone deep on a data model because something didn't add up, and has decided that the highest-leverage thing they can do next is build AI systems that fundamentally change how data science gets done . You'll build AI agents and internal systems that can increasingly handle end-to-end analysis workflows: forming hypotheses, writing and running queries, interpreting results, and drafting recommendations with the right evaluation, review, and guardrails. You'll build the retrieval infrastructure and evaluation loops that let AI systems query the warehouse reliably. You'll create workflows that detect, diagnose, and help fix data issues before they become company-wide problems. You'll build the infrastructure that multiplies what a small data team can ship. You'll join a data team that's already using AI across its work. The next step is turning those individual workflows into scalable systems, shared tools, and an AI-native operating model that becomes a benchmark for how modern data teams work. What You'll Do Build AI agents that do data science - not just SQL copilots, but systems that can safely explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations with clear evaluation and human review loops. Make AI systems query the warehouse reliably - build the retrieval infrastructure and evaluation loops that let agents use our semantic context and metadata accurately. Accelerate the AI-native data workflow - turn the best existing AI-assisted workflows into repeatable systems, reusable tools, and patterns the whole data team can adopt. Automate the data lifecycle -

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 . Data Science sits at the heart of how Coinbase builds products and makes decisions. We partner with Product, Engineering, and Design to shape roadmaps, understand our users, and move the company's bottom line through rigorous experimentation, analytics, and advanced modeling. As a Data Scientist on the Consumer team, you'll improve the customer experience across Coinbase's consumer products — including spot and advanced trading, yield, Coinbase One, international expansion, and new launches such as prediction markets and equities trading. You'll define key metrics, build measurement and causal frameworks, and translate insights directly into product strategy and shipped improvements. What you'll do: Drive analysis and deep dives on ambiguous business problems, delivering insights and recommendations that guide team decision-making Own a broad scope of data and metrics — from core logging to polished data visualizations Lead code reviews, contribute SQL and Python expertise, and maintain reliable ETL pipelines Uphold a high bar for statistical rigor, ensuring experimentation and causal analyses build genuine confidence with stakeholders Required Skills and Experience: BA/BS in a quantitative field (Math, Stats, Physics, CS, or similar) with 5+ years of relevant experience, or a PhD with 3+ years of relevant experience Proven track record of delivering impa

Job Title: Senior Data Scientist About Us “Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount . With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. WHY JOIN CAPCO? You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. MAKE AN IMPACT Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #BEYOURSELFATWORK Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. MAKE AN IMPACT Job Title: Data Scientist - Wealth Management / Retail Banking Experience: 6 to 10 Years Location: Pune / Bengaluru Employment Type: Full-Time About the Role We are seeking a highly skilled and experienced Data Scientist to join our Data Platforms team. The ideal candidate will have strong expertise in Data Science, Machine Learning, Advanced Analytics, and AI-driven solutions, with hands-on experience in the Wealth Management or Retail Banking domain or any BFSI domain.

Work Experience Required: 8 - 12 Years Experience in programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. We are accepting applications for this position until 10/16/2026 Position Overview: At Freddie Mac, you will have meaningful work to help build a better housing finance system and support homeownership and rental housing opportunities across the nation. Our internship and graduate programs provide opportunities to tackle complex challenges, contribute to strategic initiatives, and build valuable relationships with industry professionals. As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one of the nation's largest financial institutions. You will gain hands-on experience working on real-world projects, collaborating across teams, and leveraging emerging technologies – including artificial intelligence and automation—to enhance risk management practices and business outcomes. Our Impact: Enterprise Risk Management (ERM) helps build and maintain a strong, effective, and efficient risk management framework across Freddie Mac. We provide independent oversight and assessment of financial and non-financial risks while promoting a culture of accountability, innovation, and sound risk management. Our quantitative teams leverage advanced analytics, data science, modeling, automation, and emerging technologies to support enterprise-wide decision-making and risk oversight. As AI and automation continue to transform the financial services industry, our teams p