Lead Data Scientist

Overview

Lead a data science practice and its team, combining hands-on modelling, technical team management and client engagement across AI and analytics programs.

What you'll do

• Develop predictive models using machine learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-means Clustering, linear regression, PCA etc.).
• Engage with clients, understand complex problem statements, and offer solutions in the domains of Retail, Pharma, Banking, Insurance, etc.
• Contribute to internal product development initiatives related to data science.
• Develop the data science roadmap and guide data scientists to meet their deliverables.
• Handle end-to-end client AI and analytics programs.
• Drive project management for complex projects, including effort and time estimation.
• Define technology strategy and roadmap for client accounts and guide its implementation within projects.
• Run regular project reviews and audits to ensure projects are executed within agreed guardrails.
• Manage team members to ensure the project plan is adhered to over the course of the project.
• Manage client stakeholders and their expectations through a regular cadence of weekly meetings and status updates.
• Build a trusted advisor relationship with client IT management and internal accounts leadership.
• Build business cases for technological investments to meet future needs and remain competitive.
• Ensure billing and utilization of team members is maximized throughout the year.
• Allocate workload among team members, considering availability, skill set and current workload.
• Provide required inputs to sales and pre-sales activities.
• Build scalable client engagement processes for faster turnaround and higher accuracy.

What you'll need

• 8+ years of work experience.
• Experience in programming with Python, R, SQL, NoSQL and Spark, along with ML tools and cloud technology (AWS, Azure, GCP).
• Experience with Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy and BERT.
• Good understanding of statistics and ability to design statistical hypothesis testing to aid formal decision making.
• Proven ability to discover solutions hidden in large datasets and drive business results with data-based insights.
• Proactive, with full ownership of the engagement.
• Excellent written and verbal communication skills.

Nice to have

• 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.

Details

• Location: Bengaluru, Karnataka, India.