Data Analyst Jobs

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Commercial Scaled Intelligence (CSI) team is an AI-first group focused on turning data into action—building products that drive revenue growth, operational efficiency, and better outcomes for our customers, shoppers, retailers, brands, and partners. As the Ads AI Analytics Lead, you will own the intelligence behind our Ads agents. You’ll design the semantic and context layer for advertising, and build production-grade agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will collaborate closely with Ads GTM, Product, Data Science, and Engineering to ship vertical agents with measurable lift. This seat is uniquely high-impact: the tools you build are used daily by Sales, Brand Partnerships, and Ads teams, including a sales tool used by approximately 265 sellers. Yo

About the Team OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across our products. We partner with product, engineering, research, and security teams to define meaningful measures of success, understand how our systems behave in the real world, and translate evidence into better decisions. As AI agents become more capable, they can write and execute code, access sensitive systems, and complete increasingly complex tasks with greater autonomy. These capabilities create powerful opportunities to improve cybersecurity, but they also introduce risks that traditional security tools and processes were not designed to address. Meeting this moment requires new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from friction that slows users down. About the Role We are looking for a senior data scientist to help define what effective cybersecurity looks like in the age of AI agents. You will work across OpenAI’s Security organization and cybersecurity product teams to measure emerging risks, improve internal security controls, and shape AI-powered security products. The problems are foundational: How do we know whether an agent’s security controls are effective? Which safeguards meaningfully reduce risk, and which create unnecessary friction? When an AI system identifies a potential vulnerability, how do we determine whether the finding is accurate, actionable, and ultimately resolved? How do we detect anomalous behavior or risky access when the systems themselves are changing rapidly? You will report into Data Science while partnering closely with Security, Cyber Product, Engineering, and Research. This is a high-ownership role for someone who can establish a new analytical discipline, operate across organizational boundaries, and turn ambiguous security challenges into measurable improvements. In This Role You Will Define how we measure AI-agent security. Establish metrics and evaluation frame

About the Team OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale. Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise. About the Role We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security. You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty. This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up. This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support. In this role, you will Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products. Design and analyze experiments to optimize top-of

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. 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: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

About Us Paytm is India’s leading payments Super App, offering consumers and merchants a wide range of financial services. A pioneer of the mobile QR payments revolution, Paytm’s mission is to bring half a billion Indians into the mainstream economy through technology-led financial inclusion. Paytm Money is the wealth-tech arm of Paytm, enabling users to invest in mutual funds, equities, and derivatives seamlessly. Owned by One97 Communications, founded by Vijay Shekhar Sharma, the company is headquartered in Noida and backed by leading global investors. Role Overview We are looking for a strategic, business-oriented, and AI-forward Analytics Leader to drive data-led and AI-powered decision-making for Paytm Money across equities, mutual funds, and derivatives. This role will define and lead the analytics vision across user growth, trading behavior, portfolio analytics, customer lifecycle, monetization, and product experience, while partnering closely with Product, Growth, Business, Risk, and Engineering teams to scale Paytm Money’s wealth platform. The ideal candidate will bring deep expertise in financial markets, broking platforms, and investment products, along with strong experience in building scalable analytics functions. In addition, this leader should have worked intensively on AI-led modeling, predictive decision systems, AI adoption across analytics workflows, and data models designed for advanced analytics and machine learning use cases. This is not just a reporting or dashboarding role. It is a leadership role focused on building a proactive, predictive, and AI-enabled analytics engine that helps the business make faster, sharper, and more scalable decisions. Key Responsibilities 1. Analytics Strategy, AI Vision & Business Impact · Define and own the analytics and decision intelligence roadmap aligned with Paytm Money’s growth, engagement, and revenue goals. · Translate business problems across acquisition, activation, trading behavior, retention,

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. Position Overview: We are currently seeking a Quantitative Risk Analysis Manager to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with managing a team responsible for reporting and analytics regarding Collateral offerings as well as Collateral model business user supports. The role requires deep understanding of data and current code base, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for enterprise Collateral models for user acceptance testing and provide feedback. Your Impact: Manage a team of three to four people Complete baseline processes and reports monthly and interpret results as it relates to collateral risk management Follow appropriate controls and standards established to maintain and document for processes & reports. Participate in performing ad-hoc analytics in support of collateral policy Cleanse, manipulate and analyze large datasets using statistical software Collaborate with team members and interact across organizational lines to meet business objectives Qualifications: Degree in

About the Team Would you like to be part of creating a unicorn within a unicorn? Solve some of the biggest challenges facing financial inclusion of Bharat? Well, then here's your chance! Financial Services (FS) is one of the biggest new bets we are taking at Meesho on the next 10x horizon opportunity for us. Just as Ant Financial did for Alibaba, and Mercado Pago did for Mercado Libre, our vision is to build financial services for Meesho, becoming our key growth and revenue driver. We have found our Product-Market Fit, built and proved 0-1 and 1-10 journeys. Now looking for someone who can be the founding member of a 10-100-1000 journey, and this is possibly one of the most exciting and enriching experiences one could consider in their career. About the Role Meesho FS runs two lines of business: SME Lending, which offers Business Loans, and User Lending, which offers BNPL and Personal Loans (PL). User Lending is now our primary focus in this phase of our FS journey. We have 274Mn ATU, and risk management is at the core of building any sustainable credit business at scale - our being a captive audience means both Growth and Risk are an outcome of underwriting, which is owned by the Risk team. Herein also lies one of our biggest challenges: how do we assess the risk of borrowers without any credit history or income data? How can we leverage alternative information to better profile borrowers? How can we leverage our platform uniquely to create a sustained competitive advantage? This person will be responsible for driving the analytics behind these questions for User Lending - creating analytical frameworks, developing high quality analysis, driving insights and actions, and recommending policy decisions, across a well-established BNPL portfolio and a Personal Loans portfolio that is still scaling. Your role will focus on: Owning the risk for one or more segments of the portfolio while maintaining a healthy growth. Analyzing credit policies using Meesho platform data,

About the Team The Customer Experience team serves as a foundational operations pillar at DoorDash, dedicated to resolving friction within the last mile. We architect and oversee an expansive global network of support centers — spanning both teammate-assisted and AI-driven support — obsessing over the user journey to ensure every interaction is seamless and reliable. As the analytics team, our mission is to make every support interaction measurably better: we define what a great resolution looks like, quantify where we fall short, and turn that into a roadmap for product, operations, and AI/ML partners. We are looking for a Manager to lead and grow the analytics team behind our core support experience. About the Role As a Manager on the Customer Experience Analytics team, you'll set the analytical vision for how DoorDash measures and improves customer resolutions across our global network of support teammates and their interactions with our customers. You'll lead and grow a team of data scientists working at the intersection of customer experience quality and operational cost — uncovering opportunities to drive perfect interactions and informing improvements to teammate tooling that leverages AI-driven resolutions. You'll establish a clear measurement framework for resolution quality, own insights to drive strategy and roadmap, and align partners across CX, Product, Engineering, Operations, and AI/ML. This is a high-visibility leadership role: success means better outcomes for customers, a more effective support organization, and a team of data scientists who are growing in their craft. You're excited about this opportunity because you will… Lead, grow, and develop a team of data scientists — providing mentorship, feedback, and clear career development pathways. Set the analytical vision for the core support experience, defining what a great customer resolution looks like and building the metrics to measure it. Uncover opportunities to drive perfect interactions, tr

Join Delphi - Where Innovation meets transformation At Delphi, we believe in creating an environment where our people thrive. Our hybrid work model empowers you to choose where you work—whether it's from the office, your home, or a mix of both—so you can prioritize what matters most. We are committed to supporting your personal goals, family, and overall well-being while driving transformative results for our clients. We welcome exceptional talent from anywhere across the globe. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset. Rooted in the region, we specialize in delivering tailored, impactful solutions in Data, Advanced Analytics and AI, Infrastructure, Cloud Security, and Application Modernization. Whether it’s enabling predictive analytics , transforming operations with automation, or driving customer engagement with intelligent platforms, we are the trusted partner for organizations ready to embrace a smarter, more efficient future. About the role We are seeking a proactive and experienced Senior App Modernization and DevOps Engineer to lead the transformation of legacy applications and drive the implementation of modern DevOps practices on Azure. This role requires strong expertise in cloud computing, application modernization, and containerization, with a particular focus on Azure Kubernetes Service (AKS) and Azure-native solutions. The ideal candidate will have a proven track record in modernizing enterprise applications and optimizing CI/CD pipelines within a cloud-first environment. Job responsibilities Application Modernization Support: Assist in the migration and modernization of legacy applications to Azure, working closely with senior engineers to refactor, rearchitect, and containerize applications. CI/CD Pipeline Assistance: Support the development, maintenance, and optimization of CI/CD pipelines using Azure DevOps, ensuring smooth integration and deployment processes. Infras

Education: Master or Bachelor’s degree in computer science, information systems management or related field. Solution and Architecture certifications such as TOGAF or other. Experiences: More than 12+ years of experience in information technology, with 8+ years spent in data architecture or technology solutions definitions and implementations. Extensive experience in banking and financial services domain Knowledge & Skills: Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification Experiences in cloud native principals, designs and deployments. Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival Define workload migration strategies using appropriate tools Drive delivery in a matrixed environment working with various internal IT partners Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously Must be able to work independently and have skills in planning, strategy, estimation, scheduling, Strong problem solving, influencing, communication, and presentation skills, self-starter Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.) Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenki

Roles & Responsibilities Displays structured problem solving, application of right tools & techniques to solve open ended problems, Creates productized analytics solutions or frameworks independently. Understand Business & product problems and come up with deep data backed solutions. Root cause analysis and Deep dive analysis of certain product problems Running and maintaining the reporting system, presenting insights at a weekly forum Building templates, dashboards in Power BI, Gsheets for operational and management reporting Data extraction as per business request for Ad hoc analysis Business analysis and understanding Evaluating metrics to be tracked as per business goals, exploring other available metrics for deeper understanding of product performance Work in a fast-moving environment, across multiple projects with varying levels of complexity and detailing Desired Skills and Experience: 3 - 5 years working with large data sets and conducting quantitative analysis Some understanding of Statistics and prior experience of building statistical models (e.g. hypothesis testing, product experimentation, A/B Testing, regressions). Excellent knowledge SQL and intermediate knowledge of data manipulation language such as R/Python Previous experience with working on ecommerce funnels, retention Ability to think through product and business metrics to assess product features Knowledge of business modelling and basic knowledge of financial metrics, would be a bonus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines Established expertise in designing new dashboards, identifying the right metrics, layout; displays proficiency in building dashboards on Power BI using best practices and intuitive Qualifications Bachelor’s in engineering, Computer Science, Economics, Statistics, or related discipline from a reputed institute ...........................

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

Opportunity Overview: As a Staff Data Scientist at Cohere Health, you will serve as a technical leader across high-priority initiatives, shaping how data science is applied to some of the most complex challenges in healthcare. You’ll drive the design of advanced analytical and modeling solutions, influence strategic direction, and partner deeply across Product, Clinical, and Engineering to deliver scalable, high-impact outcomes. This role goes beyond execution. You’ll define approaches, set standards, and guide others in solving ambiguous, high-leverage problems. You’ll play a critical role in advancing the maturity of data science at Cohere while contributing directly to improving clinical and operational decision-making. What you’ll do: Lead the design and execution of complex, high-impact data science initiatives across multiple domains Define analytical frameworks and modeling approaches for ambiguous, strategic problem spaces Partner with senior stakeholders to shape problem definition, prioritize opportunities, and influence decision-making Develop and deploy advanced models and scalable analytical solutions that drive measurable outcomes Establish best practices for experimentation, model development, and analytical rigor across the team Mentor and guide other data scientists, providing technical leadership and elevating team capabilities Drive cross-functional alignment to ensure solutions are practical, scalable, and integrated into workflows ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitor

Opportunity Overview: We are seeking a Data Scientist to play a pivotal role in developing AI-driven healthcare enterprise applications. The ideal candidate will work with large datasets to uncover opportunities for product and process optimization. This role calls for hands-on experience in data modeling and solution optimization, along with a proven ability to deliver actionable, data-backed insights. Strong collaboration skills are essential, as you will partner with internal stakeholders and cross-functional teams to drive meaningful results. In our fast-paced environment, adaptability is key—your ability to pivot quickly and respond to business priorities will ensure you make the greatest possible impact. What you’ll do: Develop a deep understanding of business challenges and translate them into effective analytical solutions. Analyze complex datasets to uncover trends, patterns, and actionable insights that support strategic initiatives. Design, build, and maintain data models and reporting systems, leveraging both classical and modern machine learning and deep learning algorithms to enable robust analysis and informed decision-making. Evaluate and report on model performance and business impact, ensuring insights are clear, actionable, and effectively communicated. Proactively identify opportunities for product and process improvements using advanced analytics and machine learning techniques. Ensure accuracy and reliability of data-driven solutions through rigorous testing, validation, and continuous optimization. Stay ahead of industry trends by keeping up with emerging technologies and best practices in AI, machine learning, and healthcare analytics. ISMS roles and responsibilities: Fair understanding of Information Security practices. Align to the organization policies and procedures. Ensure to get updated with ISMS roles as assigned by the department/process heads. Required Qualifications: 4+ years of hands-on experience in Python with strong profic