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.