Senior Data Scientist Authentication Salary India Jobs

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

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The Data Platform team builds and operates the systems that centralize all of Coinbase's internal and third-party data, making it easy for teams across the company to access, process, and transform that data for analytics, machine learning, and powering end-user experiences. As an engineer on the team you'll contribute across the full spectrum of our systems, from foundational processing and storage to scalable pipelines to the frameworks, tools, and internal applications that make data easily and efficiently available. We have a number of open roles within the Data Platform team, each with a different focus area; read on to see if you'll be a good fit as a Data Engineering Platform Engineer. This role sits between our platform and the analysts, data scientists, and data engineers who use it every day. You'll build the SDKs, self-service apps, and abstractions that let thousands of pipelines and analyses run without those users needing to understand the plumbing underneath. What you'll do: Build clean software abstractions and modular, reusable components that let us support thousands of pipelines and beyond as we scale. Build and maintain data integration and processing SDKs used by data teams and internal services across Coinbase. Design and build self-service applications that let analysts and data scientists create, manage, and troubleshoot their own pipelines wi

Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questi ons without routing through your team. This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, setting a high bar for data-model quality and stakeholder trust. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM), taking accountability for curated data models, canonical metrics, dashboards, and Genie spaces. Treat every recurring insight as a product with an owner, a cadence, and an SLA, building a catalog of trusted, versioned data products instead of one-off rebuilds. Drive self-serve enablement by prioritizing Go

About Artefact Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works. This role combines deep, certified expertise in Google's enterprise AI stack (Gemini models, Vertex AI, and the Gemini Enterprise agent platform) with the ability to deliver end to end. Beyond your platform specialization, you will be expected to work confidently across the full delivery lifecycle — full-stack development, data engineering, cloud infrastructure, evaluation, and client communication. You will work closely with our clients, with direct exposure from the start, and you will support the professional

Senior Analytics Engineer The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call . As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Vancouver office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . What you’ll achieve Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means,

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain. We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. The Role Artefact is looking for a Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production. You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the React front end, the Python or Node service behind it, the RAG pipeline feeding it, and the evaluations proving it works. This role combines breadth and depth: the ability to take a feature from front end to cloud deployment, together with strong expertise in at least one major AI platform — Google (Gemini), Anthropic (Claude), or OpenAI. You will work with direct client exposure, and you will support the professional development of the junior engineers around you. What You'll Do Build Full-Stack AI Applications, End to End You will build AI products across the entire stack, from interface to infrastructure. Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node. Implement a

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 About the Role We are currently seeking a Senior Software Engineer to join our Agentic Analytics Platform team — the team responsible for the AI-for-Data charter inside Instacart's Data Infrastructure org. You'll design and build LLM-powered systems that transform how data practitioners (data scientists, data engineers, analysts, PMs) interact with data at Instacart — from natural-language data access and AI-assisted SQL, to automated metadata generation, to embedding intelligent capabilities across our broader data infra ecosystem. This is a hands-on role at the frontier of applied AI inside a large, modern data stack. About the Team The mission of the Instacart Self-Serve organization is to improve the productivity of data practitioners through easy-to-use, self-serve tools. Agentic Analytics is the team chartered with bringing AI and LLMs into that miss

About the Team DoorDash Ads will become the most transparent and effective advertising channel for merchants, brands, and ad buyers/agencies of all sizes to market their offerings to engaged local audiences. We build a variety of products that are easy to use and confidently generate incremental value for advertisers, while also helping consumers discover and engage with brands they love and save money. As the analytics team our goal is to advance product development, understanding of the business, and identify opportunities for the team to drive towards our north stars. About the Role As the leader of a large, high-performing team of data scientists, you’ll own the analytics strategy for DoorDash Ads for Restaurants—one of the company’s fastest-growing and most dynamic businesses. You’ll guide a team spanning multiple levels of seniority to drive insights and decisions across a multi-sided marketplace, optimizing across consumer and merchant outcomes . In your first few months, you’ll establish clear priorities, align cross-functional partners in product, engineering, sales, and strategy, and set the analytical vision for sustainable growth. Success in this role means delivering measurable business impact, elevating the quality of analytics across the organization, and building systems that balance advertiser ROI, consumer experience, and platform health. You will report into the Senior Director of Analytics on our Ads team in our Ads & Promos organization. You’re excited about this opportunity because you will… Lead and develop a high-performing analytics team, providing mentorship, feedback, and clear career development pathways. Define and drive the analytical and product roadmap by setting measurable goals and aligning cross-functional teams around success metrics. Partner closely with product, engineering, and go-to-market teams to uncover insights, optimize funnels, and inform high-impact decisions. Apply advanced analytical methods—such as co

The Opportunity Join Enigma's Growth & KYB Team at a pivotal moment as we continue to create sales and marketing solutions for small businesses. We're seeking an experienced Senior Software Engineer to develop and build innovative data products and systems that directly impact our customers and accelerate our growth. Your work will influence decisions for companies that employ half the U.S. workforce, creating tremendous value for our clients. The Role As a member of the Growth & KYB Team, you will: Design, develop and deliver data products that solve critical customer pain points and build scalable, high-quality systems that deliver rich interactions with our data. Engage with software engineers, data scientists, and product managers to create experiences that move a customer from discovery to evaluation to purchase. Analyze and extract value from data at scale, building efficient, maintainable production-grade data solutions. Create scalable and highly maintainable systems deployed in cloud environments. Own architecture and design decisions as well as hands-on implementation, ensuring that customer experiences are compelling and have low costs of ownership. What You’ll Do Operates with a bias for action and knows how to deliver value in the short, medium, and long term. Loves interacting with product teams and works hard to solve customer problems in a repeatable way. Adopts a principled, metrics-driven approach to difficult data problems and demonstrates excellence in their analytics and engineering craft. Operates transparently, collaboratively, and with low ego—loves learning from others and having their ideas questioned and challenged. Has a “can-do” attitude and thrives on a highly collaborative, cross-functional team that plays a critical role in the company’s success. Is eager to own architecture and design decisions as well as hands-on implementation. What Makes This Role Exciting? Impact : Develop products that take an innovative data-first appro

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Role Summary: This role will lead the data engineering function supporting People Analytics, including AI-assisted workforce analytics on Snowflake. This is a player-coach role requiring hands-on technical leadership plus people leadership, with strong business partnership and the ability to balance speed, quality, governance, and innovation. What you’ll do: Manage and develop data engineers Manage, coach, and grow a team of data engineers. Set expectations for quality, collaboration, delivery, and technical ownership. Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work. Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners. Stay hands on Write and review production code. Lead design reviews, code reviews, and technical problem solving. Step into critical pipelines, models, or AI workflows when needed. Build scalable People data foundations Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks. Establish team practices for documentation, lineage, data quality, and observability. Own engineering standards Set standard

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Role: We are seeking a highly skilled Full Stack Engineer to design, develop, and scale next-generation Data Quality and AI-enabled platforms. In this role, you will work across the entire technology stack—from intuitive user experiences and data visualizations to cloud-native backend services and data processing pipelines. You will partner closely with Data Quality SMEs, Data Engineers, Product Managers, Data Scientists, and Platform Teams to build solutions that support data observability, analytics, data governance, and AI-driven insights. You will help build the next generation of D&B's Data Quality Insights platform, enabling data governance, observability, analytics, and AI-powered decision support for enterprise data products.

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. ML Platform @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery, Safety, Engine, and much more. As an Infrastructure Engineer on the ML Platform team, you will design, scale, and maintain the foundational infrastructure powering our entire machine learning ecosystem. We are looking for accomplished engineers to spearhead the development of our next-generation ML tooling and platform capabilities. You will: Bootstrap and maintain Kubernetes and Cloud infrastructure for ML Platform components--Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator. Set technical strategy and oversee development of high scale and reliable infrastructure systems. Propose and implement new platform tooling to improve time to production for MLEs and Data Scientists across the full ML lifecycle. Work on infrastructure projects such as GPU fleet management, hybrid-cloud orchestration, and writing custom Kubernetes controllers and resources. Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices. Partner across organizations to build tooling, interfaces, and visualizati

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

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. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and