Data Scientist III

Snap Finance; West Valley City (UT); Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Generous paid time off

Medical, dental & vision coverage

401K with company match

Company-paid life insurance

Disability coverage

Job summary

Snap Finance is seeking a Data Scientist III to apply statistics and machine learning to consumer finance challenges and support Sales and B2B Marketing. The role is hybrid, based out of Salt Lake City area with relocation if needed.

You will design experiments, build predictive models, and deliver actionable insights from large transaction-level data, partnering with stakeholders to translate business questions into data-driven solutions.

Qualifications

• 3-5 years in a data science role or equivalent experience.
• M.S. in Statistics, Econometrics, Math, CS, or related field.
• Strong SQL skills and experience with non-relational data sources.
• Expertise in classification, regression, and clustering methods.
• Experience taking DS projects from development to production.
• Ability to deliver regular reporting and ad hoc analyses.

Responsibilities

• Design experiments and evaluation processes for business performance, new products, and features.
• Run analyses and present findings to stakeholders.
• Compile datasets, perform multidimensional aggregation, and assess business impact.
• Work with large transaction-level data to produce insights.
• Collaborate with stakeholders to mine data and deliver recommendations.
• Stay current with emerging data-tech trends.
• Mine, model, and analyze large data with predictive modeling approaches.
• Build and validate statistical models and develop new criteria.

Skills

SQL

Python

R

Statistics

Experiment design

Bayesian methods

Predictive modeling

Data visualization

Education

M.S. in quantitative field

B.S. in related field

Tools

Map-Reduce

Hadoop

Hive

Apache Spark

Job description

Snap Finance is hiring a Data Scientist III (hybrid) to apply statistics and machine learning to consumer finance problems and support Sales and B2B Marketing.

Responsibilities

• Design and implement experiments and evaluation processes for business performance, new products, and product features.
• Run analyses that incorporate project design and data collection; summarize findings and present results clearly to stakeholders.
• Compile relevant datasets, perform multidimensional aggregation, and conduct profile analysis to assess business impact.
• Work with large volumes of transaction-level data to produce actionable insights efficiently.
• Partner with stakeholders to understand business questions; build methodologies to mine and analyze data and deliver recommendations.
• Stay current with emerging technology trends.
• Mine, model, and analyze large datasets using predictive modeling approaches.
• Build and validate statistical models; provide analytic support and develop new criteria and/or strategies.

Requirements

• Ability to produce robust statistical analyses, including examples such as power analysis, hypothesis testing, experimental design, hierarchical modeling, and Bayesian and frequentist methods.
• 3-5 years in a data science role, or equivalent skills demonstrated through aligned work in another role.
• M.S. in quantitative fields, such as Statistics, Econometrics, Mathematics, Physics, Computer Science, Quantitative Social Science, Quantitative Finance, or a related discipline.
• B.S. in related fields will be considered if the skill set and experience are robust.
• Strong SQL skills, including extracting data from non-relational data sources.
• Advanced professional experience with:
  • Classification: Neural Net, Logistic Regression, Decision Trees, KNN, Random Forest
  • Regression: Linear, Nonlinear, Boosted Regression Trees
  • Clustering: K-means, Fuzzy C-means, Hierarchical Clustering, Mixture Modeling
• Demonstrated ability to take data science projects from development to production.
• Proven ability to deliver regular reporting for key stakeholder meetings, support ad hoc analysis requests, and write data-driven deep dives.
• Familiarity with concepts in consumer finance, sales operations, and B2B marketing methods.
• Expertise in one or more modeling and machine learning programming languages such as R or Python.

Technologies

• SQL
• R
• Python
• Neural Net
• Logistic Regression
• Decision Trees
• KNN
• Random Forest
• Linear
• Boosted Regression Trees
• K-means
• Fuzzy C-means
• Hierarchical Clustering
• Mixture Modeling
• Map-Reduce
• Hadoop
• Hive
• Apache Spark

Location and Work Model

• West Valley City, UT (hybrid)
• Hybrid work model based out of the Salt Lake City office
• Candidates should currently reside in the Salt Lake City area or be willing to relocate within 90 days of the start date

Benefits

• 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

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 such as Map-Reduce, Hadoop, Hive, and Apache Spark

Snap values diversity, and all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.