Lead Data Scientist
About The Position
Finicity, a Mastercard company, is leading the Open Banking Initiative to increase the Financial Health of consumers and businesses. The Data Science and Analytics team is looking for a Lead Data Scientist. The Data Science team works on Intelligent Decisioning; Financial Certainty; Attribute, Feature, and Entity Resolution; Verification Solutions and much more. Join our team to make an impact across all sectors of the economy by consistently innovating and problem-solving. The ideal candidate is passionate about leveraging data to provide high quality customer solutions. Also, the candidate is a strong technical leader who is extremely motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset.
Requirements
- 7+ years in data science/ machine learning model development and deployments
- SQL / Database experience is preferred
- Experience with Kubernetes, Containers, Docker, REST APIs, Event Streams or other delivery mechanisms.
- Familiarity with relevant technologies (e.g. GenAI, LLMs, Agentic AI, TensorFlow, Python, Sklearn, Pandas, etc.).
- Strong desire to collaborate and ability to come up with creative solutions.
- Bachelors or Master’s Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S preferred
Nice To Haves
- Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus.
- A strong understanding of NLP, Statistical Modeling, Visualization and advanced Data Science techniques/methods.
- Gain insights from text, including non-language tokens and use the thought process of annotations in text analysis.
- Solve problems that are new to the company, the financial industry and to data science
- Finance and FinTech experience preferred.
Responsibilities
- Lead, mentor and grow the data science team and tech stack focused on developing production-grade services and capabilities
- Plan and direct data science / machine learning projects within the team.
- Design and implement machine learning models for a number of financial applications including but not limited to: Transaction Classification, Temporal Analysis, Risk modeling from structured and unstructured data.
- Measure, validate, implement, monitor and improve performance of both internal and external facing machine learning models.
- Apply various Machine learning (i.e. SVM, Radom Forest, XGBoost, LightGBM, CATBoost etc), Deep learning techniques (i.e. LSTM, RNN, Transformer etc.) and LLMs to solve analytical problem statements.
- Propose creative solutions to existing challenges that are new to the company, the financial industry and to data science.
- Present technical problems and findings to business leaders internally and to clients succinctly and clearly.
- Leverage best practices in machine learning and data engineering to develop scalable solutions.
- Identify areas where resources fall short of needs and provide thoughtful and sustainable solutions to benefit the team
- Be a strong, confident, and excellent writer and speaker, able to communicate your vision and roadmap effectively to a wide variety of stakeholders
Benefits
- insurance (including medical, prescription drug, dental, vision, disability, life insurance)
- flexible spending account and health savings account
- 16 weeks of new parent leave
- up to 20 days of bereavement leave
- 80 hours of Paid Sick and Safe Time
- 25 days of vacation time
- 5 personal days
- 10 annual paid U.S. observed holidays
- 401k with a best-in-class company match
- deferred compensation for eligible roles
- fitness reimbursement or on-site fitness facilities
- eligibility for tuition reimbursement
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
