Scientist 2 Jobs

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 . 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. We are looking for a Data Scientist to join our marketing org. As a Data Scientist you introduce greater scientific rigor into the marketing measurement and optimization processes to shape Pinterest’s revenue growth and marketing strategy. The results of your work will influence and drive strategic decisions

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 . As a Data Scientist in our Core organization, you will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world. What you’ll do: Develop best practices for instrumentation and experimentation and co

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

Senior Manager, MED Oncology RWE/Epi Scientist — 4 Locations. Apply via Workday.

Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan

Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

We are looking for a Data Scientist to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-oiled machine responsible for generating key investment insights that drive trades. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of evaluating and integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in the data space. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science, machine learning, AI, and process engineering skillsets to accelerate the Quantitative Equity Team’s data preparation and modelling functions. Your specialized role will involve building, scaling, managing and evaluating our integrated data model, in direct support of alpha research. You will be supported with coaching and mentorsh

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

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

Immediate openings for IT roles in Hyderabad. Skills required: Java,Testing,Python,Devops,AWS,Fullstack, Data Scientist AI/ML, Cyber Security,Node JS,React JS.,etc (Nine Nine Eight Nine6one two73five). Its Paid Service 9989612735 Good communication & basic technical knowledge needed. Apply now with your profile.

About Anyscale At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role The Customer Engineer will play a crucial role in the customers’ post-sale journey - helping them to onboard, adopt and grow on Anyscale, troubleshooting and resolving open customer tickets and driving consumption. Anyscale is an ever evolving platform and hence will require close co-ordination with our engineering teams to debug complex issues. This is an exciting role for those who are technically curious and passionate about ML/AI, LLM, vLLM and the role of AI in next generation applications. It’s an opportunity to make a significant impact in a collaborative, fast-paced environment while building a new segment in this space. In this role, you’ll be able to Resolve customer issues and help in their successful adoption of Anyscale platform Be a technical advisor, and internal champion for our key customers Own customer issues end-to-end, from troubleshooting, triaging, escalations and eventual resolution Participate in our follow-the-sun customer support model to ensure continuity in resolving high priority tickets Keep track of open customer bugs and feature requests to influence prioritization and provide timely customer updates upon resolution Contribute towards improvement of internal tools an

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Evaluation & Annotation team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: AI model evaluation both offline and online, designing tooling and processes around human annotation, and establishing the standard around synthetics and AI generated datasets. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Evaluation & Annotation team, directly managing 4-6 engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: A Software Engineer at heart with a previous experience leading software engineering teams, as a tech lead or people manager Excellent leader with strong interpersonal skills, and the

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Training & Serving team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: distributed training of foundation models, serving at scale, designing the user experience. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Training & Serving team, directly managing 10+ engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage, infrastructure and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader Excellent leader with strong