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Mahindra & Mahindra Limited

Data Scientist

Mahindra & Mahindra Limited Chakan, Maharashtra, India

Motor Vehicle Manufacturing · 10,001+ employees

Yesterday
data-scientist Mid (2-5 yrs) Full-time India
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About the role

The candidate will design, build, and deploy machine learning models and data pipelines to drive enterprise-wide AI initiatives. They are also responsible for managing projects, prioritizing tasks, and communicating analytical findings to stakeholders.

What they look for

Python SQL Scikit-learn TensorFlow PyTorch XGBoost Machine Learning Statistical Modeling Predictive Modeling NLP Computer Vision Feature Engineering A/B Testing Data Pipelines Data Exploration Stakeholder Engagement

Requirements

Candidates must hold a degree in B.E, B.Tech, or M.Tech and possess 3-5 years of hands-on experience in data science or analytics. Strong proficiency in Python, SQL, and various machine learning libraries is required.

Full description

Job Purpose

A balanced mix of hands-on expertise as a data scientist and team management capabilities. The ideal candidate is someone who thrives at the intersection of technical depth and strategic impact. The candidate will own critical projects end-to-end to drive enterprise-wide AI initiatives.

Key Responsibilities

  • Translate high-level business problems into analytical frameworks
  • Design, build, and deploy machine learning models, statistical frameworks, and data pipelines.
  • Perform deep data exploration and generate actionable insights.
  • Work on a range of problems including predictive modeling, segmentation, recommendation systems, NLP, and computer vision depending on project needs.
  • Conduct robust feature engineering, model evaluation, and tuning.
  • Communicate findings clearly to technical and non-technical stakeholders.
  • Manage timelines, prioritize tasks, and align with cross-functional stakeholder

Skills & Qualifications

  • Degree in B.E / B.tech / M.Tech
  • 3 - 5 years of hands-on experience in data science, machine learning, or analytics
  • Strong programming skills in Python, SQL, and proficiency with libraries like scikit-learn, TensorFlow, PyTorch, or XGBoost.
  • Strong understanding of supervised/unsupervised ML, A/B testing, and statistical modeling.
  • Excellent communication, problem-solving, and stakeholder engagement skills.
  • Experience working with both structured and unstructured data at scale.

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