United Wholesale Mortgage Corp.(DBA UWM)-posted 3 months ago
Full-time • Mid Level
Pontiac, MI
5,001-10,000 employees
Credit Intermediation and Related Activities

Team members in the Machine Learning Scientist role at UWM are responsible for modeling complex problems, discovering insights and identifying opportunities using statistics, algorithms, machine learning, and visualization techniques. Data Scientists work closely with executives, product owners, SME's, and other business teams to leverage data and help answer critical business decisions. Data Scientists at UWM need to be creative thinkers and propose innovative ways to look at problems by examining and discovering new patterns within our datasets and collaborating with our business stakeholders. They will need to validate their results using an experimental and iterative approach. Perhaps most importantly, they will need to be able to communicate their insights and results to the business in a clear, concise, and approachable way. They need to be storytellers of their work. These professionals will need a combination of business focus, data programming knowledge, and strong analytical and problem solving skills, to be able to quickly develop and test hypothesis, and provide conclusions in a clear, structured manner. This role includes the full data science lifecycle from analytic problem definition, through data wrangling, analysis, model development, reporting/visualization development, testing, deployment, and feedback.

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to increase efficiency or improve the bottom line.
  • Analyze UWM data sets to identify areas of optimization and improvement of business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models, algorithms, simulations, and predictive modeling to support insights and opportunities for improvement.
  • Develop A/B testing framework and test model quality.
  • Coordinate with different business areas to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.
  • Bachelor's degree in Finance, Statistics, Economics, Data Science, Computer Science, Engineering or Mathematics, or related field.
  • 5+ years of experience in statistical analysis, and/or machine learning.
  • 5+ years of experience with one or more of the following tools: machine learning (Python, MATLAB), data wrangling skills/tools (Hadoop, Teradata, SAS, or other), statistical analysis (Python, R, SAS) and/or visualization skills/tools (PowerBI, Tableau, Qlikview).
  • 3+ years of experience collaborating with teams (either internal or external) to develop analytics solutions.
  • Strong problem solving skills.
  • Strong communication skills (interpersonal, written, and presentation).
  • Master's degree in Finance, Statistics, Economics, Data Science, Computer Science, Mathematics or related field.
  • 3+ years of experience with R, SQL, Tableau, MATLAB, Python.
  • 3+ years of professional experience in machine learning, data mining, statistical analysis, modeling, optimization.
  • Experience in Accounting, Finance, and Economics.
  • Paid Time Off (PTO) after just 30 days.
  • Additional parental and maternity leave benefits after 12 months.
  • Adoption reimbursement program.
  • Paid volunteer hours.
  • Paid training and career development.
  • Medical, dental, vision and life insurance.
  • 401k with employer match.
  • Mortgage discount and area business discounts.
  • Free membership to our large, state-of-the-art fitness center, including exercise classes such as yoga and Zumba, various sports leagues and a full-size basketball court.
  • Wellness area, including an in-house primary-care physician's office, full-time massage therapist and hair salon.
  • Gourmet cafeteria featuring homemade breakfast and lunch.
  • Convenience store featuring healthy grab-and-go snacks.
  • In-house Starbucks and Dunkin.
  • Indoor/outdoor café with Wi-Fi.
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