Data Scientist

Job Description

The Senior Data Scientist is responsible for the delivery of leading-edge analytical solutions and works closely with team members to understand the data needs of different lines of business. The Senior Data Scientist crafts solutions to support information-based decisions, produces in-depth analysis for key business issues and builds models to improve processes and for key projects.

Job Responsibilities

Below are the main job requirements and responsibilities for the Senior Data Scientist:

•    Conducts high-level reviews to identify client needs, problems and opportunities alongside other team members to determine if a possible solution can be developed.

•    Develops Analytical Briefs that summarize the methodology to be used on specific projects, highlighting key data sources, anticipated variables reviewed and expected output for the analysis.

•    Analyzes and defines use cases and requirements across business areas, identifying gaps and recommendations, and is able to translate them to analytical data applications and models using Python with clear implementation documentation.

•    Leverages SQL and other data query tools as required to pull data from multiple sources and amalgamate into new data sets for analytical and modeling purposes and evaluates key performance metrics and trends.

•    Develops analytical models for data generated by a variety of applications and products. Builds analytics applications and visualizations.

•    Performs data mining tasks, such as classification, regression, clustering, recommendations and text analysis.

Job Responsibilities (continued)

•    Builds, evaluates and improves various algorithms at the core or existing or new data driven products. Continuously identifies opportunities and solutions to better meet business needs.

•    Effectively communicates the business and technical benefits of the analytic solution to both business and technical audiences.

•    Develops and implements various types of machine learning models, segmentation strategies, data mining analyses, and performs research and development regarding new innovative analytic techniques to drive top-line and bottom-line growth.

•    In some cases, manages junior analysts, assigns and approves and certifies work, and provides coaching and development opportunities to broaden skill set and experience. 

Qualifications

Education
•    Completed post-secondary education in a related field (Math/Statistics, Economics, Engineering), graduate level preferred.

Experience
•    3 to 5 years of relevant analytics experience.
•    2 or more years’ experience in a supervisory capacity.
•    Experience with SQL, Python, AWS, Teradata and Teradata Studio is preferred.
•    Significant experience working with methodologies such as machine learning, profiling, segmentation forecasting, operations research and data mining.
•    Broad experience in business management, marketing, planning and finance, operation and project management, intimate knowledge of cross-enterprise functions and operations.
•    Demonstrated analytical experience in a marketing, operations or digital environment.

Other Candidate Requirements
•    Demonstrated ability to build an analytical plan based on a business issue (i.e., data needed, methods used, model type needed, etc.).
•    Knowledge of IT processes and infrastructure required to support business intelligence and analytics.

Other Information