Data Scientist Salary India Jobs

Senior Analyst, Big Data Analytics & Engineering — Pune, India. Apply via Workday.

About The Role & Team Amplitude is only as useful as the data inside it. The Data Connections team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import pipelines onto a durable workflow engine, building low-latency streaming export, and supporting cross-region and cross-cloud customer storage. You'll lead a team of around 10 engineers building this, reporting to our Head of Data Platform, and you'll be the person accountable for the roadmap, the reliability, and the growth of the people on it. The stack is Java, Temporal, Kafka, Kubernetes, Terraform, DynamoDB, S3, and Snowflake, running on AWS and GCP. Responsibilities Set the direction and roadmap for data import and export, with clear priorities and tradeoffs you can explain to engineers, PMs, and customers Lead, coach, and grow a team of around 10 engineers — hiring, career development, feedback, and performance Partner with your tech leads on architecture across ingestion, transformation, and delivery, without becoming the bottleneck for every decision Own reliability, SLOs, and cost efficiency for pipelines customers depend on daily Expand the set of destinations and sources we support, and make each new integration cheaper to build than the last Work directly with Product, Design, and other Data Platform teams to ship e

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As the Staff Product Manager, Data Platform at Vanta, you will be responsible for product strategy and direction for Vanta’s data platform. You’ll sit between the core platform and feature teams, driving the roadmap for transforming how we fetch, store, and use data from customers and 3rd parties at scale. This platform directly enables customer and business outcomes, and backs Vanta’s products and experiences. This is a highly impactful, technical role at the center of how Vanta works and meets customer needs at real scale. Vanta manages data from over 16,000 customers and is rapidly scaling daily. You’ll be part of Vanta’s Automation group, which owns how customers discover and connect to other platforms through integrations, use that data to power product experiences and tests, drive customers toward compliance-related security outcomes, and ultimately generate the evidence required for audit. You aren’t building Vanta’s service delivery platform - you’re building the engine that powers compliance and monitoring outcomes. Your team will be Foundations, which has wide scope and depth, and you’ll be the sole PM to support the data platform. What you’ll do as Staff Product Manager, Data Platform at Vanta: Own the impactful Data Platform roadmap, pairing closely with engineering counterparts to plan durable platform investments that serve our customers and products built on top of customer data Collaborate closely with other product teams to understand what platform investments they need to be successful, get ahead of their roadmaps, and create a plan that balances short and long term needs to support customer outcomes. Directly

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Staff Software Engineers identify key strategic technical initiatives, deliver significant value to our customers and business, and set the tone for engineering excellence and culture. As an early engineering hire on the growing Privacy & Data Security team based in London, you will play a key role in bolstering our engineering presence in Europe. You'll partner with product management, product design, and your growing engineering team to drive the discovery and development of privacy features that expand Vanta’s value for its customers. Your work will accelerate product development and create a consistent customer experience for all of our customer segments. Vanta’s team and technology surface are growing quickly, and it’s essential that we invest in the right abstractions and systems to enable us to scale with our business. As a Staff Software Engineer, you’ll be responsible for identifying key strategic technical initiatives that impact our entire engineering team and deliver significant value to our business. You will set a high bar for engineering culture and excellence, and your past experience will be leveraged to enable and accelerate Vanta’s growth. Our business has found incredible product-market fit and has monetized effectively since the day we signed our first customer. We’re growing at a blistering pace, which presents career-defining opportunities for engineers to accelerate their growth and to contribute to a rapidly-scaling company. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. We’d love for you to join us! What you’ll d

Assoc Director, IT Data and AI Product Owner — Ireland - Cork. Apply via Workday.

Senior Manager, Master Data Governance - Data Lead — Ireland - Cork. Apply via Workday.

Manager, IT Data, ML & AI Engineering — United States - North Carolina - Raleigh. Apply via Workday.

Sr Manager, IT Data Engineering — United States - North Carolina - Raleigh. Apply via Workday.

Assoc Director, IT Data Engineering — United States - North Carolina - Raleigh. Apply via Workday.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Member of Technical Staff in Data Analysis and Evaluation, you will play a pivotal role in ensuring the quality, reliability, and performance of our large language models (LLMs). Your primary focus will be on designing and conducting data collection tasks, assessing and evaluating dataset quality, and analysing the robustness and generalisability of our models. You will work closely with cross-functional teams, including researchers, engineers, and data annotators, to conduct data-driven decision-making and improve the overall effectiveness of our AI systems. This role combines expertise in statistics, experimental design incl. human annotators, and machine learning to ensure that our models are trained on high-quality data and perform reliably across diverse scenarios. You will contribute to Cohere’s mission of advancing AI by ensuring our systems are robust, scalable, and impactful. Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role. As a Member of Technical Staff

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the data infrastructure behind some of the most demanding AI training workloads in the world, and we want sharp, curious people to help us do it. In this role, you'll build and maintain the high-performance data layer our Modeling teams rely on for training and evaluation jobs. As a Software Engineer, Data Infrastructure, you will: Work directly on petabyte-scale storage infrastructure, and the networking and performance challenges that come with it. Collaborate daily with researchers and engineers who are some of the best in the world at what they do. You may be a good fit if you have: 4+ years of experience working on data storage infrastructure Strong command of Python Kubernetes experience, especially on the storage side (Persistent Volumes, CSI drivers, etc.) The ability to transform unstructured data into performant datasets across diverse storage backends including S3, GCS, and POSIX Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink [Nice-to-have] Familiarity with modern analytics tooling such as BigQuery, Airflow, or dbt Genuine excitement about AI.

We are looking for a Lead, Data Development, AI Platform to lead the team building and operating the technical platform behind Hootsuite's Analytics MCP. This includes routing infrastructure, orchestration services, agent infrastructure, and data pipelines that enable reliable AI-driven analysis at scale. You will set technical direction for the team, strengthen engineering practices, and translate target architecture and integration standards into secure, production-grade systems that Data Analytics & AI teams can confidently build on. This is a hands-on technical leadership role. You will stay close to the code while owning delivery outcomes, engineering quality, and the team's culture of craft and accountability. You will develop strong, well-reasoned recommendations on how the platform and orchestration architecture should evolve, seek approval at the Senior Manager and Director level, and then guide the team through disciplined execution. You will also partner closely with AI Context & Integration and AI Data Architecture to ensure the platform, context layer, semantic layer, and downstream agent workflows operate as one coherent system. WHAT YOU’LL DO: Lead the design and delivery of the orchestration layer that connects the Analytics MCP platform across its most complex surfaces, including query execution across schemas and models, federated data access between the data warehouse and external source systems, and multi-step agent workflows for cross-functional business processes. Develop clear technical recommendations for platform and orchestration architecture evolution, align those recommendations with Senior Manager and Director-level direction, and guide the team through disciplined execution within the approved architecture. Own the operational reliability, scalability, quality, and observability standards for core Analytics MCP components, including routing and agent infrastructure. Guide the team to build and operate these systems to prod

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About The Role Data governance is one of the most critical challenges for Mixpanel's enterprise customers, and the AI era turns it into a foundational problem. Analytics and agents are only as trustworthy as the data beneath them. Poor data quality compounds: incorrect analyses spread as it becomes easier for anyone — or any agent — to query data, and the problem multiplies as customers scale into projects with high-cardinality events and fast-growing user bases. A data foundation that stays clean, consistent, and trusted is what sets Mixpanel apart. As a Senior Software Engineer on the Data Foundation team, you'll work across the stack to build high-impact features with extreme customer focus. You'll partner closely with engineers across the company, and with Design, Product, and GTM, to solve one of the hardest problems in analytics: keeping data clean, consistent, and trustworthy at scale. Curious what this looks like in practice? Read why data governance matters for AI-powered analytics on our blog. What You'll Do Build customer-facing features on our web application (React SPA) Collaborate closely with engineers and cross-functional partners across Product, Design, GTM, and beyond Take full ownership of projects — from shaping and delivery through iteration We're Looking For Someone Who Has Full-stack experience, with deep expertise in at least one of: Web application backends (Python, Django) High-volume APIs Search indexing A track record of leading projects end to end, not just executing tickets Comfort moving across the stack Bonus Points For Experience with data ingestion (Go) A data-driv

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are a team of high-output generalists where ML and systems engineering converge to push autonomy performance forward. As a Senior Perception ML Data Infrastructure Engineer, you will own the critical bridge between our autonomous vehicle hardware, our human labeling operations, and our ML models. You will take ownership of our core native perception data platform. This is not a standard web development role; the stack is deeply adjacent to our core robotics infrastructure. You will be dealing with massive, dense 3D point clouds at a scale that pushes the boundaries of industry state-of-the-art, alongside complex sensor parsing, pipeline propagation, and rigid performance constraints. You will operate in highly ambiguous environments, inheriting complex systems, establishing strict API boundaries, and building the "good enough, fast enough" infrastructure that guarantees our ML models learn from high-quality data. About the wo

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment. About the Work Design and develop unified, introspectable, large-scale batch and streaming data processing systems that can ingest and process data across a wide range of use cases relevant to evaluation. Create and implement a storage system capable of accommodating both the large volume and diverse r