Lead Data Scientist

Responsibilities:

• Work directly with application/product teams to define, develop, and implement the right ML solution for the problem at hand.
• Come up with new solutions for solving automotive industry business problems.
• Define the correct evaluation metrics for offline and online evaluations.
• Creating and tracking accuracy and performance metrics.
• Incorporating new data sources and implementing creative methodologies to improve model performance.
• Helping build production systems that take inputs from multiple models and support decision-making.
• Should be equally comfortable digging into customer requirements as you are drilling into the design with development teams and developing production-ready learning models.
• Should consistently bring strong, data-driven business and technical judgment to decisions.

Requirements:

• Masters, Ph. D. in data science, mathematics, operations research, or a related field.
• The right candidate has a background in probability and statistics, applied mathematics, or computational science and a history of solving difficult problems with good business impact using a scientific approach.
• Experience working with ML algorithms and frameworks.
• Significant experience in data science and machine learning with a strong proven track record in delivering positive business impact.
• 5+ years of hands-on experience with analytics, data science, and big data in a business context.
• Experience in programming in Python or similar languages and maintaining code repositories in Git.
• Experience with data visualization and presentation turns complex analysis into insights.
• Experience in recommendation engines and natural language processing.
• Domain knowledge of the automotive industry.
• Enjoys discovering and solving problems; proactively seeking clarification of requirements and direction; and being a self-starter who takes responsibility when required.
• Strong interpersonal, verbal, visual, and presentation skills, ability to communicate complex findings simply to executives.
• Ability to work collaboratively across multiple product and application teams.
• A willingness to learn, share, and improve.