General Summary

Elevate is a globally distributed technology firm which develops next-generation financial products focused on managing life’s everyday expenses.  The Data Science team conceptualizes, develops, deploys, and maintains predictive models using advanced statistical and machine learning methods. These models are used in Elevate’s Underwriting, Account Management, and Operations applications.  The Sr. Data Scientist plays a critical role by applying cutting-edge modeling techniques to drive growth, control risk, and ensure operations excellence.

Primary Responsibilities

• Design, Develop and Deploy advanced machine learning and Artificial Intelligence algorithms/predictive models for use in Underwriting, Customer Management, Marketing, and Operations;
• Assess, clean, merge, and analyze large datasets adhering to standardized data manipulation techniques and methodology by leveraging R, Python and/or Apache Spark;
• Perform parallel processing computations both within R as well as cluster computing technologies such as Apache Spark.
• Design, Develop and Deploy multiple linear and nonlinear algorithms for testing, development and deployment into our underwriting engine in the application of risk management in all of Elevate’s acquisition channels;
• Efficiently apply data mining methodologies to minimize credit/fraud losses, maximize response and approval rates, and develop methods to enhance profitability of Elevate products;
• Successfully implement scoring models on multiple decision platforms Including R instance deployment, On premise deployment and cloud deployment and multiple forms such as Java objects, R Object Models and Apache Spark Models;
• Provide knowledge, insight and guidance of third party data providers such as Transunion, Clarity/Experian and Equifax to include knowledge of products and data available, products to purchase or discontinue, cost benefit analysis of retrospective analysis, effective use of variables, data dictionaries as well as advantages and limitations;
• Maintain clear, detailed model documentation on our Wiki Server by leveraging reproducible research technologies such as Rmarkdown, IPython, Jupyter Notebook, etc.;
• Functional lead and point of contact with business partners to support the needs and goals of all Elevate portfolios, Rock teams, Braintrusts and Pods.
• Lead analytical projects by leveraging and coaching Jr Data Scientists.

Experience and Education

• Minimum Master’s degree in highly quantitative field (Statistics, Economics, Mathematics, Engineering, or other quantitatively-oriented degree) required.
• At least three years of experience in Data Science or Modeling for consumer lending; Professional experience waived with at least two years of Data Science or Modeling experience and Ph.D. Degree in highly quantitative field (Statistics, Economics, Mathematics, or other quantitatively-oriented degree)
• Experience with third-party consumer credit data and non-FCRA compliant consumer data;
• Demonstrated proficiency with advanced statistical modeling and substantial experience with machine learning techniques (e.g., Random Forest, Gradient Boosting, LASSO, Elastic Net, etc). Knowledge of penalized regression and classification methods a plus;
• Strong data skills, with ability to conduct substantial data munging/engineering.
• Proficiency with Linux and R, Python, or Java; expertise with versioning software (e.g., Git), big data solutions and data processing frameworks (e.g., Spark, Hadoop);
• Experience with at least four database technologies such as MSSQL Server, SAS Datasets, Hadoop, Apache Hive/Impala, Spark, Redshift, HBASE, Kafka, Spark Streaming, Neo4j, Teradata, Oracle, MySQL, DB2, Amazon AWS, Cassandra, PostgreSQL, NoSQL, JSON & XML parsing, etc.
• Proven experience working in fast-paced environment with ever-changing demands
• Superior communication skills for communication with Risk Management peers and executive team
• Proficiency of contemporary supervised and unsupervised data mining techniques a plus

Required Skills, Abilities, Soft Skill Factors

• Motivation Skills - History of achieving aggressive organizational goals and objectives, conveying sense of urgency while moving beyond challenges and obstacles. 
• Thinking and Administrative Skills - Solid analytical and problem solving skills.  Ability to analyze trends and suggest solutions to challenges. 
• Achieve Successful Results – Takes the initiative to get things done.
• Demonstrates Adaptability – Works effectively in the face of stress, ambiguity, difficult situations and shifting priorities
• Innovates – Challenges the status quo thinking to generate new ideas; takes open minded approach to situations.
• Communication Skills - Refined written and verbal communication skills.  Ability to foster open communications, listen effectively and build strong partnership networks.
• Technological Competence – Extensive knowledge of R, Python, Scala, Java, SAS, MATLAB, SQL, and/or SPSS and risk management technology with the ability to leverage such tools to improve the organization’s decision making criteria.

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