Lead Data Scientist

Candidates MUST go on-site at one of the following locations

Columbus, OH

Cincinnati, OH

Cleveland, OH

Indianapolis, IN

Hagerstown, MD

Chicago, IL

Detroit, MI

Minnetonka, MN

Houston, TX

Charlotte, NC

Akron, OH

Experience:

· Master’s degree and 5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, experience with big data analysis tools and techniques, and experience building and deploying predictive models, web scraping, and scalable data pipelines

· Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling

Python, R, or SAS SQL and some sort of lending experience (i.e. HELOC, Mortgage etc) is most important

Excellent communication skills

If a candidate has cred card experience (i.e. Discover or Bread financial ) THEY ARE A+ fit!

Education:

Master’s degree or PhD in computer science, statistics, economics or related fields

Responsibilities:

· Prioritizes analytical projects based on business value and technological readiness

Performs large-scale experimentation and build data-driven models to answer business questions

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence

Evangelizes best practices to analytics and products teams

Acts as the go-to resource for machine learning across a range of business needs

Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring

Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization

Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs

Anticipates and analyzes trends in technology while assessing the emerging technology’s impact(s)

Coaches' individuals through change and serves as a role model

Skills:

· Up-to-date knowledge of machine learning and data analytics tools and techniques

Strong knowledge in predictive modeling methodology

Experienced at leveraging both structured and unstructured data sources

Willingness and ability to learn new technologies on the job

Demonstrated ability to communicate complex results to technical and non-technical audiences

Strategic, intellectually curious thinker with focus on outcomes

Professional image with the ability to form relationships across functions

Ability to train more junior analysts regarding day-to-day activities, as necessary

Proven ability to lead cross-functional teams

Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)

Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)

Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL)

Financial Services background preferred