Lead Data Scientist

Summary

The role is expected to serve as the primary client-facing data science lead to design, build, and scale advanced AI and machine learning solutions for enterprise clients. This role combines strong hands‑on expertise in generative AI, NLP, machine learning, and data engineering with consulting maturity, stakeholder management, and solution ownership. The position emphasizes a mix of client advisory, model development, cross-functional collaboration, and measurable business impact.

• Work Experience:
  
  4-8 years

• Experience in programming (Python, R, SQL, No
  
  SQL, Spark) with ML tools & cloud technology (AWS, Azure, GCP) with Time Series Forecasting
• Prior experience in forecasting, predictive analytics, or demand planning projects
• Develop and deploy time series forecasting models for business and operational use cases
• Experience in Python libraries such as numpy, pandas, scikit-learn, tensor‑flow, scapy, scrapy, BERT, etc.
• Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making
• Develop predictive models using machine learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K‑means Clustering, linear regression, PCA, etc.)
• Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc.
• Contribute to internal product development initiatives related to data science
• Develop data science roadmap, and guide data scientists to meet their deliverables
• Handling end-to-end client AI & analytics programs. Your role will be a combination of hands‑on contribution, technical team management, and client interaction
• Proven ability to discover solutions hidden in large datasets and to drive business results with data‑based insights
• Drive excellent project management required to deliver complex projects, including effort/time estimation
• Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy
• Define technology/strategy and roadmap for client accounts, and guide implementation of that strategy within projects
• Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders
• Manage the team members, to ensure that the project plan is being adhered to over the course of the project
• Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates
• Build a trusted advisor relationship with the IT management at clients and internal accounts leadership
• Build business case for technological investments to be made for future needs and to remain competitive
• Ensure that billing and utilization of team members is maximized throughout the year

• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and unstructured data ecosystems
• Comfortable with large scale data processing and distributed computing
• Allocate workload among team members and by taking into consideration employee availability, skill set, and current workload when making assignments
• Providing required inputs to sales, and pre‑sales activities
• Excellent written and verbal communication skills