Lead Data Scientist

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 4200000 (ie INR 25-42 LPA)

Min Experience: 4 years

Location: Bengaluru

JobType: full-time

We are looking for a highly skilled and motivated Lead Data Scientist to join our growing data team. The ideal candidate will bring strong expertise in machine learning, data science using Python, and end-to-end model development to lead high-impact projects that drive business insights and innovation. You will work closely with cross-functional teams including engineering, product, and business stakeholders to identify opportunities, formulate data-driven solutions, and deploy models at scale.

Requirements

Key Responsibilities:

• Lead and own the entire lifecycle of data science projects — from problem definition and data exploration to model development, validation, and deployment.
• Develop, implement, and optimize machine learning models using Python-based data science libraries and frameworks (e.g., Pandas, Scikit-learn, NumPy, TensorFlow, PyTorch).
• Collaborate with engineering teams to deploy models into production systems and monitor their performance post-deployment.
• Conduct exploratory data analysis (EDA) to derive insights, identify patterns, and uncover business opportunities.
• Work with large and complex datasets using efficient data processing techniques, ensuring data quality and integrity throughout the pipeline.
• Lead data-driven initiatives and mentor junior data scientists on technical and strategic project execution.
• Present results and insights to business stakeholders in a clear and impactful manner, driving actionable recommendations.
• Continuously research and evaluate new tools, technologies, and methodologies to improve the team’s capabilities and outcomes.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
• 4–9 years of hands-on experience in data science, machine learning, and Python for data science applications.
• Strong proficiency in Python and its data science stack — Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, etc.
• Solid understanding of machine learning algorithms including supervised, unsupervised, and ensemble methods.
• Experience building and deploying ML models in production environments.
• Good knowledge of data wrangling, feature engineering, model tuning, and evaluation techniques.
• Familiarity with version control systems (e.g., Git), cloud platforms (e.g., AWS, GCP, or Azure), and ML Ops best practices is a plus.
• Excellent problem-solving skills and ability to break down complex problems into actionable solutions.
• Strong communication and collaboration skills, with the ability to lead technical discussions and influence stakeholders.

Preferred Skills:

• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Familiarity with distributed data processing (e.g., Spark or Dask).
• Exposure to business intelligence tools and data visualization platforms like Power BI or Tableau.