Top Data Science Jobs in Delhi

The Manager, Analytics & Data Science will oversee analytics initiatives, develop solutions for risk management, and communicate insights effectively to stakeholders.

The Senior Analyst will deliver analysis aligned with client objectives, develop data science solutions, lead meetings, and build client relationships.

The Lead Analyst leads customer analysis, manages a team of analysts, conducts data preparation, and provides insights using data science methods.

Lead and manage customer analysis, mentor analysts, conduct data preparation, apply data science methods, and communicate findings to clients.

The Data Scientist will analyze and model data for ML systems, focusing on Personalization and Recommendation Engines, and collaborate with teams to enhance data-driven solutions.

The Proposal Leader drives strategy and governance for complex proposals, aligning solutions with client outcomes and improving win rates in ServiceNow consulting deals.

The Sr. Analyst role involves developing data science solutions, leading sales meetings, building client relationships, and communicating insights to achieve business objectives.

The Senior Data Scientist will enhance the predictive modeling capabilities of Lyric's platform, focusing on machine learning and statistical methods for supply chain optimization.

The User Researcher will lead research projects from discovery to synthesis, using various methods to gain insights that improve products while collaborating with stakeholders.

Lead a team of engineers in developing financial services, collaborating with stakeholders to build effective systems, and fostering a culture of innovation and excellence.

Deliver analysis supporting client objectives through data science solutions; lead meetings, build relationships, and communicate insights for growth.

The role involves using scientific expertise to evaluate AI-driven life science tools, designing criteria for AI solutions, and ensuring alignment with scientific data and customer needs.

The role involves leading tech project management for theft detection initiatives, collaborating with executives, and coordinating cross-functional teams to ensure project success.

As a Product Engineer, you will ensure quality and usability of geospatial AI tools, design test plans, validate software, and document technical processes.

As a Product Researcher, you'll plan and conduct user research, deliver insights for product decisions, and collaborate with teams to improve user experience across Coursera's enterprise workflows.

The Principal Engineer, Data Science will lead data science projects focusing on predictive modeling, cloud solutions, and machine learning techniques while collaborating on technical designs to meet client requirements.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

The role involves overseeing data science projects, mentoring team members, and developing solutions using machine learning and data technologies, while ensuring alignment with client requirements.

The role involves leading machine learning initiatives, designing solutions, and collaborating with stakeholders to enhance business value through data.

Design and optimize prompts for AI systems, evaluate model performance, collaborate with teams on machine learning strategies, and document best practices.

Lead AI and data innovation by developing ML models, optimizing data systems, and mentoring junior team members in a collaborative team environment.

The Senior Staff Engineer, Data Science role involves guiding team direction, solving complex challenges for clients, and leveraging technical expertise to innovate solutions.

The Principal Engineer, Data Science role involves leading data science projects and providing strategic insights using extensive IT experience.

The role involves designing data science solutions, mentoring team members, deploying models, and ensuring high-quality code. It requires strong analytical skills and the ability to communicate technical requirements effectively.

Lead and manage the AI & Data Science function, set technical strategy, deliver AI solutions, collaborate across teams, and communicate impact to stakeholders.