Data Scientist Jobs in Delhi, India

Weekday AI Client team focuses on delivering advanced analytics solutions for diverse industries. As a Data Scientist you will apply AI/ML techniques to solve complex business problems, design and deploy scalable data products, and collaborate with cross‑functional teams to deliver impactful insights.

ERM is seeking a Technical Consultant Level 3 – Data Scientist / Automation Specialist to lead the development and deployment of advanced data engineering and automation solutions. The role blends technical leadership, cloud architecture expertise, and cross‑functional collaboration to support ERM’s global initiatives.

ERM is hiring a Data Scientist/Automation Specialist to support data-driven solutions across environmental and sustainability projects. The role focuses on developing and maintaining Python scripts and automation workflows, applying NLP and image processing to extract insights from PDFs, DOCX, and images, building ETL pipelines with Apache Airflow and PySpark, and deploying solutions on Azure, AWS, and GCP. Candidates will also assist in OCR workflows, machine learning model development, and collaborate with project teams to ensure data quality.

Data Scientist/Automation role at ERM India focuses on building automated data pipelines and applying advanced analytics to support environmental consulting. The position requires developing Python scripts, orchestrating workflows with Apache Airflow and PySpark, and deploying solutions on Azure, AWS, or GCP. Candidates will extract insights from unstructured documents using NLP and OCR, build ETL pipelines, and collaborate with cross‑functional teams to ensure data quality and integrity.

Rockwell Automation is a global technology leader focused on helping manufacturers be more productive, sustainable, and agile. The Data Scientist role supports IoT Foundation infrastructure and Connected Enterprise projects, developing advanced AI/ML models, collaborating with cross-functional teams, and ensuring production release of data science solutions across multiple locations in India.

Data Science team at Ericsson develops innovative machine learning solutions to solve complex business challenges. The role builds predictive models, recommendation engines, and deep learning systems while collaborating with business leaders to define success metrics.

Data Scientist on Ericsson's AI/ML team, developing machine learning solutions to solve complex business problems. The role builds predictive models, recommendation engines, and deep learning systems while collaborating with business leaders to define success metrics.

Environmental Engineering team at WSP focuses on advanced analytics for air quality solutions. The Data Scientist designs, builds, and deploys machine learning models and robust data pipelines to enable data‑driven decisions across environmental projects.

Barclays Fraud Analytics team focuses on detecting and preventing fraudulent activities across customer accounts. As a Data Scientist you will design and build data pipelines, investigate data quality issues, and develop KPIs to measure fraud prevention effectiveness, collaborating with internal stakeholders and law enforcement.

Data Science team at EXL drives AI transformation by building agentic GenAI solutions for enterprise impact. The role leads design and deployment of large language model workflows, architects scalable APIs, and mentors engineers while collaborating with cross‑functional stakeholders.

Data Science & Analysis team at EXL builds enterprise AI solutions leveraging LLMs and advanced analytics. The Data Scientist designs, develops, and deploys scalable ML/AI applications, creates FastAPI services, and implements vector database pipelines while collaborating with UI/UX and BI teams.

Fractal Analytics Data Science team builds cutting‑edge generative AI solutions using large language models. The Data Scientist designs and implements end‑to‑end LLM applications, develops code libraries and frameworks, and collaborates with cross‑functional teams to integrate AI features into core systems.

Fractal Analytics’ Gen AI team builds advanced LLM solutions for enterprise clients. The Data Scientist designs, implements, and maintains end‑to‑end generative AI pipelines, from research to production deployment, collaborating with cross‑functional teams to integrate models into core systems.

AI Labs at Transaction Network Services (TNS) builds scalable AI solutions for global logistics. As a Data Scientist Apprentice, you will develop and deploy predictive models, perform feature engineering, and collaborate with software engineers to integrate ML into production.

WSP Air Quality Analytics team drives data‑centric solutions for environmental projects. The Data Scientist builds and validates predictive models, designs scalable data pipelines, and translates insights into actionable recommendations for cross‑functional stakeholders.

GenAI - Data Science team at EXL builds advanced LLM‑powered solutions to solve complex business problems. The role designs and evaluates summarization, classification, extraction, and conversational assistants, crafting prompt strategies and RAG architectures.

Data Scientist on Thales Digital India, building AI solutions for cyber & digital business. Develop regression, classification, and segmentation models, design end‑to‑end ML pipelines on Databricks, and deploy models on GCP. Work in Noida, India, onsite with a focus on large‑scale data and Generative AI.

Lead data science initiatives at Barclays Capital Securities, driving strategic decisions through advanced analytics, machine learning, and predictive modeling. Oversee data pipeline development, statistical analysis, and stakeholder collaboration to optimize operations and innovation across banking functions.

Data Scientist 3 – Machine learning & Python at Adobe. Independent engineer who scopes business problems, builds production‑ready ML solutions, and drives insights to predictive modeling.

Data Scientists at Clearwater Analytics leverage statistics, machine learning, and visualization to derive insights and build predictive models. They identify valuable data sources, automate collection, preprocess structured and unstructured data, analyze large datasets to uncover trends, build machine‑learning algorithms, and present findings with visualization techniques.