Sr. Data Scientist

4 days ago

Kandivali Mumbai Maharashtra, India Mahindra & Mahindra Ltd Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Sr. Data Scientist

Date: 6 Oct 2025

Location:MITC, Kandivli, MITC, Kandivli, IN

Company: Mahindra & Mahindra Ltd

Job Purpose

We are looking for a Senior Data Scientist with a balanced mix of hands-on expertise and team leadership capabilities. The ideal candidate is someone who thrives at the intersection of technical depth and strategic impact. In this dual role, you'll own critical projects end-to-end while mentoring a team of data scientists and analysts to drive enterprise-wide AI initiatives.

Key Responsibilities:

Leadership (50%)

  • Lead and mentor a small team of junior to mid-level data scientists and analysts.
  • Translate high-level business problems into analytical frameworks and guide project execution.
  • Review models, code, and outputs to ensure quality and scalability.
  • Manage timelines, prioritize tasks, and align with cross-functional stakeholders.
  • Collaborate with product, engineering, and business teams to deliver AI-driven solutions.

Individual Contributor (50%)

  • 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.

Skills & Qualifications

Required Qualifications:

  • 5–8 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.

  • Solid understanding of supervised/unsupervised ML, A/B testing, and statistical modeling.
  • Demonstrated experience in leading or mentoring data science teams (formal or informal).
  • Excellent communication, problem-solving, and stakeholder engagement skills.
  • Experience working with both structured and unstructured data at scale.

Good to Have:

  • Exposure to cloud-based AI/ML platforms such as AWS SageMaker, Google Vertex AI, or Azure

ML Studio.

  • Experience working with cloud-native data tools (e.g., BigQuery, Redshift, Snowflake).
  • Understanding of data architecture and modern database systems (e.g., PostgreSQL, MongoDB,

Cassandra).

  • Familiarity with MLOps practices, model monitoring, and CI/CD pipelines for ML.

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