Lead Data Scientist

This role is for one of the Weekday's clients

As a Lead Data Scientist, you will be at the forefront of AI/ML innovation, leading by example with a strong hands-on approach in Machine Learning, Generative AI, Python, and SQL, along with experience in cloud environments (GCP, Azure, or AWS). This role blends technical expertise with leadership, requiring you to mentor a high-performing team while actively contributing to end-to-end AI/ML project execution. You will work cross-functionally to develop cutting-edge AI solutions that solve complex business challenges. If you excel in a fast-paced environment and enjoy transforming business problems into scalable AI-driven solutions, this role is for you!

Requirements

Key Responsibilities:

AI/ML Development & Deployment:

• Develop and implement ML models, Generative AI solutions, and predictive analytics.
• Conduct data mining, feature engineering, and statistical analysis.
• Own project roadmaps, ensuring quality control and timely delivery.
• Work closely with Data Engineering teams to deploy and operationalize ML models.
• Automate and optimize ML workflows for efficiency.

AI/ML Strategy & Innovation:

• Drive the growth of the Data Science practice, building new AI/ML capabilities.
• Design industry-specific AI/ML solutions and contribute to thought leadership.
• Evaluate emerging AI technologies and trends, integrating them into business solutions.
• Lead research initiatives, exploring new AI innovations and applications.

Leadership & Team Development:

• Mentor and develop a high-performance Data Science team.
• Provide guidance on career growth and skill development.
• Collaborate with cross-functional teams to drive seamless execution of AI initiatives.

Required Skills & Qualifications:

• 8+ years of experience in Data Science & AI, with strong expertise in ML, Generative AI, Python, and SQL.
• In-depth knowledge of ML algorithms (Classification, Regression, Forecasting, NLP, LLMs, Optimization, etc.).
• Experience with end-to-end ML deployment, including Azure, AWS, GCP, or Databricks.
• Proven ability to solve complex business problems in industries such as Retail, CPG, BFSI, Healthcare, or eCommerce.
• Strong foundation in statistics, probability, stochastic processes, and causal inference.
• Excellent communication skills, with the ability to explain AI concepts to non-technical stakeholders.
• Experience with big data tools (Hadoop, Hive, PySpark) and ML pipelines.
• Bonus: Experience in Google Analytics, Adobe Analytics, or digital marketing analytics.
• Bachelor's/Master’s degree in Computer Science, Statistics, Mathematics, Operations Research, or a related field.