Job Description

Snap Finance is looking to strengthen its dynamic, growing analytics department. We are seeking a dedicated Data Scientist III with a passion for statistics, machine learning, and solving real-world problems with robust data. The ideal candidate understands how to apply the practices of data science to understand a problem and generate significant value through powerful predictive models. This role is tailored for working within a consumer finance company, specifically focusing on supporting the Sales and B2B Marketing departments.

How you’ll make an impact:

• Data Mining and Modeling:
  • Mining, modeling, and analyzing large datasets, utilizing predictive modeling techniques.
  • Building and validating a variety of statistical models, providing analytic support, and developing new criteria and/or strategies.

• Experimental Design and Evaluation:
  • Design and implement experiments and processes for evaluating business performance, new products, and product features.
  • Conducting required analyses incorporating project design, data collection, and analysis, summarizing findings, and presenting results in an understandable manner.

• Business Impact Analysis:
  • Compiling appropriate data, applying multidimensional data aggregation, and performing profile analysis to evaluate business impact.
  • Handling large volumes of transaction-level data to derive actionable results efficiently.

• Stakeholder Interaction:
  • Interacting with stakeholders to understand their business questions, crafting methodologies to mine/analyze datasets, and delivering insightful recommendations.
  • Keeping up to date with the latest technology trends.

What you’ll need to succeed:

• 3-5 years working in a data science position or performing work that aligns with the required skills in another position.
• M.S. in quantitative fields such as Statistics, Econometrics, Mathematics, Physics, Computer Science, Quantitative Social Science, Quantitative Finance, or another related field.
• B.S. in the fields described above will be considered if the skill set and experience are robust.
• Expertise in one or more modeling/machine learning programming languages such as R or Python.
• Strong SQL skills and the ability to extract data from non-relational data sources.
• Advanced understanding and professional experience with the following methods:

• Classification methods (e.g., Neural Net, Logistic Regression, Decision Trees, KNN, Random Forest).
• Regression methods (e.g., Linear, Nonlinear, Boosted Regression Trees).
• Clustering methods (e.g., K-means, Fuzzy C-means, Hierarchical Clustering, Mixture Modeling).

• Ability to generate robust statistical analyses (e.g., power analysis, hypothesis testing, experimental design, hierarchical modeling, Bayesian and frequentist methods).
• Demonstrated ability to take data science projects from development to production.
• Skilled analyst who produces regular reporting content for key stakeholder meetings, responds to ad hoc analysis requests, and generates insightful deep dives.
• Familiarity and experience with concepts in consumer finance, sales operations, and B2B marketing methods.

What would make you stand out:

• Experience with a variety of data structures and databases (SQL, no-SQL, graph, etc.).
• Knowledge about Big Data related techniques (e.g., Map-Reduce, Hadoop, Hive, Apache Spark).

Why Join Us:

• Generous paid time off

• Competitive medical, dental & vision coverage

• 401K with company match for US

• Company-paid life insurance

• Company-paid short-term and long-term disability

• Access to mental health and wellness resources

• Company-paid volunteer time to do good in your community

• Legal coverage and other supplemental options

• A value-based culture where growth opportunities are endless