Lead Data Scientist, Upgrade

• This role requires a strong foundation in statistics, machine learning, and financial domain knowledge
• Advanced Degree (MS/PhD) in Data Science, Engineering, Statistics, Mathematics, Computer Science, or a related quantitative discipline
• 5-10 years of hands-on experience in a data science or analytics role, preferably in financial services
• Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL
• Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.)
• Detail oriented and strong analytical skill set
• Proactive, driven, and ability to work in a fast-paced environment

Desirable

• We are seeking a highly analytical and results-driven team member to join our growing data science team in the financial services sector
• You will play a key role in developing and implementing predictive machine learning /AI models, leading data-driven decision-making processes, managing data science projects from conception to deployment, and extracting insights that drive product development, risk mitigation, and customer strategy
• Build and deploy ML/AI models to solve business problems in areas like prospect targeting, credit risk, fraud detection, pricing, verification and loss forecasting
• Analyze large, structured and unstructured datasets using SQL, Python or similar tools
• Evaluate existing customer data, new third party or alternative data to enhance the feature list and work with data engineering and analytics teams to build scalable and durable feature engineering process
• Stay up to date with the latest trends and technologies in data science and fintech, actively research new tools and techniques available for model development
• Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies