Senior Data Scientist

Responsibilities: Apply advanced analytics techniques to extract actionable value from business data. Design and run large-scale experimentation and build data-driven models to address business questions. Research and evaluate cutting-edge machine learning, deep learning, and AI methods and tooling. Define requirements used to train, improve, and evolve deep learning models and algorithms. Develop and communicate a vision and roadmap for expanding data exploitation across the organization. Support product teams with data-based recommendations through presentations and clear analysis. Share and promote analytics and product best practices. Own the full model development lifecycle: identify business requirements, source data, fit models, present results, and deliver production scoring. Perform other duties as assigned.

Requirements: Master’s Degree incomputer science, statistics, economics, or related fields .3+ yearsof work and/or educational experience inmachine learning or cloud computing .Experience using statistics and machine learning to solvecomplex business problems .Experience conducting statistical analysis usingadvanced statistical software .Experience withscripting languages and packages .Experience building and deployingpredictive models .Experience withweb scraping .Experience working withscalable data pipelines .Experience withbig data analysis tools and techniques .TechnologiesR, RStudio, Python, SAS, SQLNoSQLAWS Sagemaker TensorFlow, scikit-learncaret

Preferred Qualifications: Up-to-date knowledge of machine learning and data analytics tools and techniques. Strong predictive modeling methodology. Experience leveraging bothstructured and unstructured data sources .Willingness and ability to learn new technologies on the job. Ability to communicate complex results to both technical and non-technical audiences. Ability to work effectively in teams and independently across multiple tasks while meeting aggressive timelines. Strategic, intellectually curious approach focused on outcomes. Professional image and ability to build relationships across functions. Strong experience with R/RStudio, Python, SAS, SQL, NoSQL.Strong experience with cloud machine learning technologies (for example, AWS Sagemaker).Strong experience with machine learning environments (for example, TensorFlow, scikit-learn, caret).Strong understanding of statistical methods, including Bayesian Networks Inference, linear and non-linear regression, hierarchical models, and hierarchical/mixed models or multi-level modeling. Financial Services background.

Exempt status: YesWorkplace type: