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About the Role:

Finicity, a Mastercard company, is recognized as a pioneer and leader in Financial Data Access, FinTech, Data Science and Decisioning. Consumers should have full transparency and control of their Financial Data. Finicity expands financial inclusion and increases financial and data literacy. Finicity’s solutions provide Intelligence and real-time access to Financial data.

Finicity’s Data Science teams focus 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. Check out Experian Boost, UltraFICO and the recent announcement from Mastercard for more!

Ideally, the Lead Data Scientist will bring expertise to advance our team’s Production Data Science for internal and external client-facing edge-services. This team is changing industries with advanced Data Science and AI enabled financial interactions and transactions.

What you will do:

As a Lead Data Scientist, you will empower consumers and businesses to create value and growth. You will own and design models and will work to deploy solutions to Financial Institutions, FinTechs, Small and Medium Businesses, Large Enterprises Consumers and even Government agencies and related Ecosystems. This particular role’s primary focus is creating services for transaction classification, categorization and tagging capabilities and solutions. These solutions include lending, decisioning, financial management, and payment services. The underlying services are Verification Services, Entity Resolution, Attribute and Temporal Analysis and more.

Primary responsibilities include:

  • Plan and direct data science / machine learning projects within the team.
  • Lead, mentor and grow data science teams focused on developing production-grade services and capabilities.
  • 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.
  • Analyze massive amounts of data to provide insights.
  • Propose creative solutions to existing challenges that are new to the company, the financial industry and to data science.
  • Present findings to business leaders internally and to clients.
  • Leverage best practices in machine learning and data engineering to develop scalable solutions.

Job Requirements / Qualifications

Required

  • Bachelor's Degree or higher in Computer Science or Data Science.  Master's preferred.
  • 3-8+ years commercial machine/deep learning and modeling experience. Combinations of Software/Data Engineering may be considered with sufficient ML experience.
  • Strong understanding of statistical modeling, NLP, visualization and advanced data science techniques/methods.
  • Focus on interpretation and validation of results.
  • Mid-senior level Python coding experience required.
  • Excellent written and oral communication skills on technical & non-technical topics.
  • Experience in leading projects and mentoring teams of data scientists and analysts.

Preferred

  • Senior level software development, data science or data engineering programming is highly desired.
  • Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus.
  • A strong understanding of Natural Language Understanding, Computer Vision, Statistical Modeling, Visualization and advanced Data Science techniques/methods.
  • Gain insights from text, including non-language tokens and use the thought process of image 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.

Skills

  • Experience in applying a wide range of machine learning algorithms to real life problems.
  • Familiarity with relevant technologies (e.g. Tensorflow, Python, Sklearn, Pandas, etc.).
  • Strong ability to interpret, analyze and visualize large amounts of data.
  • Strong desire to collaborate and ability to come up with creative solutions.
  • Ability to work independently as well as in a team environment.
  • Willingness to learn new tools and flexibility to adapt.

Location: Salt Lake City / Hybrid or Remote

About Finicity:

Finicity, a Mastercard company, helps individuals, families, and organizations make smarter financial decisions through safe and secure access to fast, high-quality data. Our trusted and proven open banking platform empowers consumers to easily connect their financial data to the apps they choose, transforming the way we experience money for everything from budgeting and payments to investing and lending.

Through market-leading data connections, Finicity partners with influential financial institutions and disruptive fintech providers alike to give consumers a leg up in a complicated financial world, helping to improve financial literacy, expand financial inclusion, and ultimately lead to better outcomes. Finicity is headquartered in Salt Lake City, Utah.

Finicity provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.