Data Scientist II-2

Role Overview

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 Data Scientist II. 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.

Responsibilities

• Manipulates large data sets and applies various technical and statistical analytical techniques (e.g. OLS, multinomial logistic regression, LDA, clustering, segmentation) to draw insights from large datasets.
• Apply various Machine learning (i.e. SVM, Radom Forest, XGBoost, LightGBM, CATBoost etc), Deep learning techniques (i.e. LSTM, RNN, Transformer etc.) to solve analytical problem statement.
• 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.
• 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 science 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 analysis, vision and roadmap effectively to a wide variety of stakeholders.

Requirements

• 3-5 years in data science/ machine learning model development and deployments
• 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
• SQL / Database experience is preferred
• Experience with Kubernetes, Containers, Docker, REST APIs, Event Streams or other delivery mechanisms.
• Familiarity with relevant technologies (e.g. Tensorflow, Python, Sklearn, Pandas, etc.).
• Strong desire to collaborate and ability to come up with creative solutions.
• Additional Finance and FinTech experience preferred.
• Bachelor’s or Master’s Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics.

Skills

• Python
• Machine Learning
• Deep Learning
• NLP
• SQL