Data Scientist

Mahindra Mahindra Limited.

Posted: 5 months ago
Openings: 10
Applicants: 0

Job Description

A Data Scientist with 1 3 years of experience is responsible for collecting, analyzing, and interpreting large datasets using advanced analytics, machine learning, and cloud-based technologies. The role focuses on deriving actionable insights, building predictive models including those using large language models (LLMs) and supporting business decision-making by working with a modern data and AI/ML tech stack, including Python, GCP, AWS, Azure, LangChain, and both SQL and NoSQL databases like MongoDB.

Key Responsibilities

Gather, clean, and preprocess structured and unstructured data from multiple sources.
Analyze large datasets to identify trends, patterns, and actionable business insights.
Develop, implement, and maintain machine learning and AI/LLM-based models (including prompt engineering and RAG/agent-based models) using frameworks such as LangChain, AutoGPT, CrewAI.
Build data pipelines and manage data ingestion for scalable solutions across GCP, AWS, and Azure platforms.
Work with both relational and NoSQL databases (example MongoDB) to store and manipulate data efficiently.
Create automated scripts and tools in Python for data analysis, model evaluation, and deployment.
Communicate findings through clear reports, dashboards, and data visualizations for technical and non-technical stakeholders.
Collaborate with cross-functional teams, including data engineers, business analysts, and product managers, to propose and implement data-driven solutions.
Stay updated with the latest advancements in AI, machine learning, and cloud technologies.

Required Skills Qualifications

bachelors degree (or higher) in Computer Science, Engineering, Statistics, Mathematics, or related field.
1 3 years of practical experience as a Data Scientist or in a related data/AI role.
Proficiency in Python (including libraries like NumPy, Pandas, Scikit-learn, and Matplotlib).
Hands-on experience with LLMs, GenAI models, LangChain, and prompt engineering.
Experience with cloud platforms: Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure.
Familiarity with data storage technologies, especially MongoDB (NoSQL) as we'll as SQL databases.
Ability to design, build, and deploy end-to-end machine learning/data science solutions using modern MLOps practices.
Strong analytical and problem-solving skills; ability to interpret and communicate complex findings.
Excellent written and verbal communication skills; teamwork and collaboration abilities.

Preferred/Bonus Skills

Experience with additional cloud-native AI/ML services and MLOps frameworks.
Knowledge of APIs (eg, Flask, FastAPI) for model deployment.
Familiarity with other big data tools (Spark, Hadoop), and additional ML frameworks (TensorFlow, PyTorch) is advantageous