Senior Data Scientist - Remote

Reposted 18 Days Ago
Hiring Remotely in Utah, USA
Remote
Mid level
Fintech
The Role
The Data Scientist II will analyze large datasets, develop predictive models, evaluate business performance, and interact with stakeholders to provide insights.
Summary Generated by Built In

Company Overview:

At Snap Finance, we believe everyone deserves access to the things they need, regardless of credit history. Since 2012, we've used data, machine learning, and a more human approach to create flexible financing solutions that help people move forward. We're proud of our inclusive, supportive culture, built on empowering our customers, partners, and team members alike. When our people thrive, so does our innovation.

If you're looking to make an impact and grow with a team that values you, come join us!

Job Description

Position Overview:

Snap Finance is looking to strengthen its dynamic, growing analytics department. We are seeking a dedicated Senior 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:

  • 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

More:

Snap values diversity and all qualified applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. Learn more by visiting our website at www.snapfinance.com.

California Residents, please review our California Consumer Privacy Act Notice at https://snapfinance.com/ccpa-notice 

Top Skills

Spark
Hadoop
Hive
Python
R
SQL
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The Company
Salt Lake City, UT
664 Employees
Year Founded: 2012

What We Do

Snap Finance is a rapidly growing digital-finance company that specializes in providing consumer financing and rent-to-own purchase options. This company is technology driven; the IT platform is the backbone for running our operations and is critical to driving cost efficiency. With over 10 years of experience in the financial industry, Snap provides merchandise financing to brick and mortar as well as e-commerce merchants. The Snap lease-purchase agreement is an innovative financial product which gives the 40% of consumers with poor credit an alternative to payday loans and other high-risk financial products to acquire needed or desired merchandise. Snap Finance secured the largest bank revolving credit facility ever for a private consumer lease-to-own company. The credit facility from BMO Harris Bank will enable Snap Finance to service more than $1 billion in lease-to-own finance agreements.

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