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Data Science Manager Salary India Jobs

8,306 active opportunities · Updated for October 2026

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Explore current data science manager salary india jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Pinterest
📍 United States• Full-time• Remote• From $145.7K/yr
1mo ago

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 . The Platforms TPM organization partners with Experimentation, ML, LLM/GenAI, and Data Infrastructure teams to shape how Pinterest measures everything that matters — from product experiments to AI systems to the platforms everyone builds on. What you'll do: As a Staff Technical Program Manager for Measurement, you'll have the rare opportunity to shape how a company the size of Pinterest measures itself — turning a portfolio spanning experimentation, machine learning, generative AI, and data infrastructure into one coherent, high-impact program. Drive Pinterest's experimentation roadmap — accelerating how confidently and quickly teams can test, learn, and ship new ideas at scale. Own the program driving cost and compute efficiency across our ML systems, and help scale data science workflows into production-grade tooling. Lead cost optimization and

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Stitch Fix
📍 United States• Full-time• Remote• From $200K/yr
1mo ago

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems. We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on. Responsibilities: Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points. Likewise, actively shape the product roadmap for direct client-facing styling experiences, expand

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S
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We’re looking for a Senior Manager to lead our App Experience & Marketplace Data Science team in the Product organization. You will lead a team covering app experience (UI, growth platform, analyst/admin/data engineer tools and experience) and data marketplace areas. Well designed high value apps are essential to make it simple for our customers to complete billions of SQL queries, deploy python, and use powerful AI tools every day Data marketplace makes it easy with a click of a button to get access to a wide range of 3rd party data instead of having to contact a sales representative at a data vendor and setup and maintain a complex API. All the projects above allow the data scientist to work on very large datasets, and a variety of diverse interesting projects that span the domains of data engineering, analytics, statistics, and machine learning. In this role, you will both lead a team, and be hands-on as a tech lead in this area. The manager will interact frequently with senior management, product managers, and engineering managers. The ability to effectively communicate complex technical ideas to a wide audience is crucial. IN THIS ROLE YOU WILL: Serve as the tech lead/manager of a Data Science team in the Product organization, leveraging AI tools and functions (e.g

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DU
DoorDash USA
📍 San Francisco• Full-time
15 days ago

About the Team Merchant Analytics helps DoorDash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. We work across some of DoorDash’s most important merchant and marketplace priorities, building the measurement, insights, and decision frameworks that improve outcomes for merchants and drive company impact. About the Role We’re hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact. You will report into Director, Data Science on our Merchant Analytics team in our Analytics organization. You’re excited about this opportunity because you will… Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time. We’re excited

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Figma
📍 Ca New York• Full-time• From $235K/yr
1mo ago

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The AI Products Data Science org is at the center of next generation products within Figma. With a charge to uplevel Figma’s use of data, the team works alongside other Data Scientists and Engineering to identify ways to implement and democratize new statistical methods, build data frameworks, and incorporate data within Figma’s product development process. The team contributes to the company’s goals by collaborating closely with product managers, engineers, and our finance team to uncover new opportunities, identify inefficiencies and recommend improvements through data-driven insights. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Lead, support, and grow a team of data scientists and data science managers with varied strengths and expertise focused on product strategy, internal tooling, and Impact measurement Champion data quality, accessibility, and the democratization of data across the company Establish trust within and across teams by creating accountability and a positive work environment in partnership with other leaders in the organization Partner with Product, Engineering, Design, Research, Sales, Marketing, or Finance to drive impact We'd love to hear from you if you have: 5+ years of experience managing and leading high-output data science teams, including scaling teams in high-growth environments 7+ years of experience in Analytics, Data Science, or a related field, with experience working on AI tools or

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Dropbox
📍 Canada Select Locations• Full-time• Remote• From C$209.1K/yr
1mo ago

Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for Dropbox’s underlying data foundations that power our business as a whole. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy. Cost & Efficiency: Own the unit economics of the data platform — compute and storage efficiency — and drive measurable improvements without sacrificing reliability. Cross-Functional Partnership: Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast. Engineering Culture: Establish rigorous engineering practices

REMOTEci/cdgitai
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D
Dropbox
📍 Us Select Locations• Full-time• Remote• From $202.7K/yr
1mo ago

Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for Dropbox’s underlying data foundations that power our business as a whole. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Responsibilities Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy. Cost & Efficiency: Own the unit economics of the data platform — compute and storage efficiency — and drive measurable improvements without sacrificing reliability. Cross-Functional Partnership: Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast. Engineering Culture: Establish rigorous engineering practices — code review, testing, CI/CD for data, incident response, and postmortems — and champion the effective, measured use of AI coding tools to improve engineering productivity. Team Leadership: Lead, mentor, and grow

REMOTEci/cdaigo
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About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the Team: We are the Central Data and AI Product team, responsible for building and managing the analytical products and datasets that power decision-making across Paytm. We’re rebuilding how analytics gets done at the company. As a central product team, we drive the build and adoption of our data platform in close partnership with consumer teams across business verticals (Online Payments and Offline Payments) and functions (Growth, Risk, Data Science). About the Role: This is a senior Data Product Management role for someone who enjoys marrying business analytics problems to simplified data design solutions. You will own a portfolio within the Central Data and AI Product charter, lead a small, high-leverage team (1–2 PMs and 1 analyst), and partner with engineering and business stakeholders to ship products that scale across the organisation. Key Responsibilities: * Lead and grow a team of product managers and analysts (1–2 PMs and 1 analyst) — hiring, coaching, performance management, and career development. * Drive the end-to-end data product development lifecycle — from discovery and scoping through delivery, adoption, and iteration. * Define and articulate the product vision, strategy, and roadmap in alignment with company goals and market trends. * Partner with cross-functional teams — business, growth, risk, and data science — to understand customer needs and align product offerings to work cleanly with agentic analytical workflows. * Work closely with engineering on technical design, development, sprint planning, and prioritisation across our stack (AWS, Spark, EMR, EC2, Hive, Trino, Superset)

sqlawsgit
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O
OneTrust
📍 Atlanta• Full-time• From $153.8K/yr
15 days ago

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge As Senior Manager, Data Engineering and Platform you will be a people leader of a team of Data Engineers responsible for creating platform and data engineering architecture for business intelligence and data science solutions. This role will have a substantial focus on coaching and people management alongside a strong individual contributor component in hands-on data engineering. Your Mission You will work closely with other team members like data architects and business analysts to understand what the business is trying to achieve, move data from source to target, and design optimal data models. Develop and adhere to standard methodologies: platform architecture, data engineering, data quality, analysis, validation to ensure the team provides quality work to company and build trust with analytics solutions. Propose and socialize data architecture to enable OneTrust business analytics. Drive technical conversations with stakeholders to explore all facets of problem and solution. Solve immediate production issues with an eye to solve things for long-t

pythonsqlaws
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O
18 days ago

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

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A
1mo ago

About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management role. We are looking for a leader with a solid data science and statistical foundation who can connect advances in experimentation methodology with scalable production systems. You will help set our technical and scientific direction, translating new statistical methods and machine learning research into capabilities that customers can use reliably at scale. You’ll partner closely with data scientists, engineers, product managers, and customers to advance the state of experimentation. The ideal candidate is equally comfortable discussing causal inference and statistical power with data scientists, distributed computation architectures with engineers, and experimentation strategy with customers. What You’ll Do Lead and grow the team responsible for Statsig’s data ingestion, experiment computation, and stats engine. Define the technical and scientific strategy for advancing experimentation across both Statsig Cloud and warehouse-native deployments. Partner with data scientists and engineers to turn new statistical and causal inference methods into scalable, reliable product capabilities. Evolve our data and computatio

restmachine learningai
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Justworks
📍 New York• Full-time• $240K – $310K/yr
1mo ago

Who We Are At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset - our people. We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you. We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team. Our Values If this sounds like you, you’ll fit right in. Department Technology, Data & AI About The Team The Data & Analytics team is Justworks' data and AI center of excellence — a connected set of functions spanning business intelligence, data science, analytics engineering, platform data/ML engineering and AI builders. We've grown significantly over the last several years and continue to build momentum across the business, leveling up maturity in how we deliver insights, govern data, and enable the company to make better decisions. You'll find a highly collaborative & diverse group motivated by craft, shared learning, and a genuine commitment to growing our impact for customers while evolving how we work together for our people. Come build with us! The Data Platform Engineering team sits at the core of this foundation, owning the pipelines, platform infrastructure, and reliability that every other DNA function depends on. Who You Are You're a hands-on engineering leader with deep experience building and operating modern data platforms. You've led teams through scale — evolving architecture, improving reliability, and making hard tradeoffs between speed, cost, and quality. You're as

pythonsqlaws
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