Data Scientist Salary India Jobs

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. THE MISSION We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps—you will define them. At the intersection of autonomous agents and large language models (LLMs) , you will build the models and systems that turn enterprise data into self-directed, decision-making agents —shifting from passive data access to autonomous execution. Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems , including: Arctic LLM : Enterprise foundation models optimized for performance and efficiency Arctic-Text2SQL : Post-trained reasoning models with frontier-level quality at a fraction of cost and latency Snowflake Intelligence : Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization Arctic Inference : High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex Arctic Long-Context Training : Enables 1M+ token context training on a single H200 GPU Agent World Models (AWM) : RL training across 1,000+ synthetic environments for tool-using agents We focus on core challenges such as reliable re

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

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 In this role, you will be a member of the Perception & Behavior team, leveraging the cutting edge of machine learning research to solve challenging real-world robotics problems. This role is focused on bringing advancements in the field of ML and large-scale learning to the AV domain, moving towards a more end-to-end autonomous driving system. This role requires working with and developing large models for perception and behavior, keeping up-to-date and experimenting with state-of-the-art architectures quickly and efficiently, collaborating with other teams to determine data and infrastructure support needs, and working to improve model optimization and inference speeds. You will use your applied research skills to think through the creation and deployment of these ML models on our autonomous vehicles while working alongside talented researchers in the field. If you love solving fundamental AI challenges and deploying your s

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

About the Team The Personality & Model Behavior team, within OpenAI’s broader Personal AGI team conducts research on how to shape personalities and guide the behavior of models. We think about topics such as emotional intelligence, reasoning, and how models interact thoughtfully with users. We’re particularly interested in understanding how individual users want ChatGPT to behave, and creating personalized models that feel uniquely tailored to each user. We integrate this research into ChatGPT and other OpenAI products that are used by hundreds of millions of users. About the Role We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models, and in areas like reinforcement learning and reward modeling. An ideal candidate is passionate about product-driven research. In this role, you will: Conduct research around personalization, personality, and model behavior by leveraging and developing tools such as synthetic data, reward modeling, and reinforcement learning. Build robust evaluations and model training pipelines to facilitate our research. Innovate new post-training methods. 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. You might thrive in this role if you: Have a deep understanding of machine learning and its applications. Have prior knowledge in training and optimizing models and building evaluations. Are willing to dive into large ML codebases to debug issues. Thrive in dynamic and technically complex environments. Have a track record of delivering innovative, out-of-the-box solutions to address real-world constraints. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through o

About the Team The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. 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: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modelin

About the Team The Personalization-Memory team, within OpenAI's broader Personal AGI organization, is focused on developing agents that can learn from prior interactions in order to become more helpful and efficient over time. We build general-purpose memory and personalization capabilities that transfer across ChatGPT and other agentic products, and we collaborate with applied engineering on the product surfaces that allow users to interact with memory. About the Role As a Research Engineer / Research Scientist on the Personalization-Memory team, you will research and develop improvements to memory usage and personalization in OpenAI's frontier models. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a truly personalized ChatGPT. We're looking for individuals who have a background in frontier model post-training, are able to iterate quickly, and who are passionate about product-driven research. 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: Own and pursue a research agenda for improving memory use and personalization in frontier models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. Collaborate closely with the research and product teams to influence the shape of technical solutions in the product. You might thrive in this role if you: Are passionate about personalization and building personalized assistants. Have experience working with user signals and human data to turn feedback into reliable signals for training and evaluation. Have a deep understanding of frontier model post-training and machine learning applications. Value principled approaches and research craftsmanship. Are comfortable diving into a lar

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Lead, Senior Decision Scientist serves as a strategic analytics and ideation leader supporting Payment Integrity Affordability initiatives with a primary focus on Fraud, Waste & Error (FWE) and Special Investigations Unit (SIU) programs. This role provides leadership and guidance to a team of Decision Scientists while driving the development, evaluation, and implementation of innovative opportunities that improve affordability outcomes and strengthen Payment Integrity capabilities. The Lead Decision Scientist is responsible for establishing analytical frameworks, managing ideation pipelines, defining success metrics, and identifying cross-functional opportunities that create enterprise value across Payment Integrity programs. Required Qualifications 7+ years of experience in healthcare analytics, Payment Integrity, Fraud, Waste & Error (FWE), Special Investigations, or related healthcare operations. 5+ years of experience leading analytical projects or providing technical leadership within a healthcare environment. Demonstrated experience working with healthcare claims platforms including ACAS, QNXT, HRP, or comparable systems. Experience using SAS, SQL, Python, R, or other analytical and statistical programming languages. Experience performing advanced data analysis, opportunity identification, trend analy

About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. 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: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI systems About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an ex

Ignite your curiosity. Solve the unsolvable. At Leidos, we do more than write code—we decode the unknown. Our San Diego-based research and engineering team takes on some of the nation’s toughest defense challenges using advanced signal processing, ocean remote sensing, and high-performance computing. We’re seeking a Software Engineer / Computer Scientist who enjoys solving complex problems and pushing the limits of performance. In this role, you’ll work alongside a multidisciplinary team of scientists and engineers with expertise in hydrodynamics, physics, acoustics, and signal processing to build impactful software that turns massive, complex data sets into meaningful insight. If you are motivated by innovation, energized by collaboration, and excited to see your work support real-world missions, this could be the right opportunity for you. What You’ll Do Collaborate with scientists and engineers to design, develop, and optimize advanced algorithms for next-generation radar, optical, and infrared sensor systems. Build scalable, high-performance backend systems for scientific computing in distributed environments. Integrate, refactor, and improve scientific codebases to increase efficiency and scalability. Translate and optimize existing code for GPU/CUDA acceleration and parallel or distributed execution. Test, document, maintain, and enhance complex software in Linux/Unix environments. Contribute in a collaborative environment that values technical excellence, creativity, and continuous growth. Required Qualifications Bachelor’s degree in Computer Science, Applied Mathematics, Physics, or a related field with 4+ years of backend software development experience, or a Master’s degree with 2+ years of experience. Equivalent experience may be considered in place of a degree. U.S. citizenship and the ability to obtain a Top Secret clearance; active Top Secret clea

ROLE SUMMARY The Clinician Medical Monitor is accountable for providing medical and scientific expertise and oversight for Clinical Trials and serves as a single point of accountability for design, execution, monitoring, delivery and reporting of one or more clinical studies and to ensure patient safety. The clinician medical monitor may be required to design a development strategy for multiple protocols designed to obtain worldwide approval for a compound or group of compounds. In addition to study level activities, the clinician medical monitor may participate in standing committees, review compounds for potential in-licensing, including performance of due diligence reviews, and aid new business development on market opportunities and the target product profile. ROLE RESPONSIBILITIES Accountable for safety across the study Provide study team with medical advice for all medical issues during risk assessment and mitigation planning to enable quality, compliance and patient safety at the trial, site and patient level. Ensures development of and adherence to the Safety Surveillance Review Plan (SSRP). Consistent with the SSRP, performs and documents regular review of individual subject safety data, and performs review of cumulative safety data with the safety risk lead. As appropriate, the clinician medical monitor may delegate these responsibilities to the study clinician scientist identified in the SSRP. The specific components of safety data review are detailed in the appropriate SOPs and the “Safety Data Review Guide – for Clinicians.” Monitor study safety issues and provide input to serious adverse events (SAEs) reports. Provides appropriate medical context in terms of risk factors, medical history and other important medical factors required to put the SAE or AE into appropriate medical context required for benefit-risk assessm

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role Search is being rebuilt in real time. Millions of people now start with a question to ChatGPT, Claude, Gemini, or Perplexity, and the answer they get decides which products they try. When someone asks how to build an app, a website, or a tool for their business, Replit needs to be the answer. We're hiring an AEO/GEO/SEO Lead to own how Replit gets discovered, across AI-generated answers and traditional search. This is a zero-to-one role. You'll define the strategy, then execute it yourself with AI-leveraged production, agency partners, and cross-functional teams behind you. You'll work daily with our Web, Growth, Brand, Content, Product, Engineering, and Analytics teams. The fastest-growing AI-native companies have already turned AI answers into a primary acquisition channel. Your mandate is to do the same for Replit: grow AI referral traffic into one of our largest sources of new builders, keep our traditional search presence compounding, and make Replit the platform AI assistants recommend when anyone wants to build software. Replit moves fast. We ship continuously, experiment relentlessly, and aim to make every builder more productive and creative. We're looking for someone who thrives in that environment: part strategist, part operator, part scientist of a channel that changes every month. What You'll Do Own the AEO/GEO Strategy Define where Replit must show up across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews, for which prompts and buyer intents, and build the playbook to win those answers. Set targets, sequence the roadmap, and defend the strategy with data. Win Citations Across the Open Web LLMs cite what they trust: Reddit threads, YouTube videos, high-authority publications, co

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Growth Platform team’s vision is to drive long term sustainable growth for the Airbnb community. Our mission is to build a best-in-class agentic system, and capabilities to support the growth of all Airbnb products, current and future. We achieve this by delivering highly personalized and relevant content and product experiences to the Airbnb community, both on and off of the Airbnb platform. The north star is full autonomy — where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human intervention. We are progressing along a deliberate maturity curve: AI assisted → agentic → autonomous, with human-in-the-loop controls at every stage to ensure brand safety, quality, and compliance. The Growth Platform deeply integrates with the Airbnb product, understanding the customer journey and enabling differentiated customer engagement experiences to drive product growth. The platform also powers digital marketing channels including landing pages, email, push, SMS, and digital advertising, as well as the machine learning/AI and data platforms that feed into the management and optimization of these channels. The Difference You Will Make: As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. We're seeking a Senior Staff Engineer who thri

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and