Sr. Data Scientist
Role details
Job location
Tech stack
Job description
Snap Finance is looking to strengthen its dynamic, growing analytics department. We are seeking a dedicated Sr. Data Scientist 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:
- D esign 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.
Requirements
- 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).
Benefits & conditions
Health insurance, 401(k) matching, Paid time off, Vision insurance, Dental insurance, Life insurance, Disability insurance, 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