The Manager of Data Science and Analytics works under the general direction of the Vice President of Information Technology to support our Executive Leadership team with insights gained from analyzing company data. The Manager of Data Science and Analytics is adept at using large data sets to deliver executive management dashboards, find opportunities for product and process optimization and use models to test the effectiveness of different courses of action. They will lead and enable the Data Analytics/Business Intelligence team to utilize a variety of data mining/data analysis methods, and database platforms, build and implement models, use/create algorithms and create/run simulations and create data interpretation tools for executives and senior management. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. He or she will possess strong communication skills and must be knowledgeable working with both technology and business partners across the organization in a collaborative manner, managing expectations and requirements of stakeholders.
Reports To: Vice President of Information Technology (direct line) and Executive Leadership (dotted line)
Coordinates: Data Analytics/Business Intelligence Projects, Strategic Data Warehouse Initiatives, Dashboard Development, reporting teams and various committees
Supervises: Programmer Analyst, Data Analyst, Data Science Interns and Database Programmer
Works with executives and stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mines and analyzes data from company databases to drive optimization and improvement of report development, marketing techniques and business strategies.
Coordinates research and analytic activities utilizing various data points (unstructured and structured) and employs programming to clean, massage, and organize the data.
Develops and maintains Data Analytics/Business Intelligence Projects, Dashboard Development projects and schedules to manage programs through the entire data lifecycle. This includes planning, scoping and budgeting, project control and status reporting, team management, problem resolution and risk management to ensure completion of projects are on schedule and within budget.
Responsible for Strategic Data Warehouse Initiative. Works closely with all business units to develop long term data platform architecture (plan, budget, and execution).
Drives the execution of multiple business plans and strategic objectives by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly.
Assesses the effectiveness and ensures accuracy of new data sources and data gathering techniques.
Defines company data assets and develops custom models and algorithms to apply to data sets.
Uses predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develops company A/B testing framework and tests model quality.
Coordinates with different functional teams to implement models and monitor outcomes. Develops processes and tools to monitor and analyze model performance and data accuracy.
Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and cost effectiveness; and participating in and supporting community outreach events.
Provides supervision and development opportunities for the Data Analytics Team by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and ensuring diversity awareness.
Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity.
Vendors, Consultants, and Technology Companies: To evaluate and implement data models, database platforms, reporting tools, and related monitoring
Job Knowledge, Training and Education
Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields
5-7 years of experience manipulating data sets, building statistical models, working with and creating data architectures.
Proficient in SQL
Proficient in Microsoft PowerBI
Proficient in variety of programming languages and frameworks (Java, C++, Python, R, Hadoop, Spark, Azure, etc.)
Experience working closely with senior managers, business leaders, decision-makers, and other stakeholders in their projects and software products.
Advanced knowledge with conducting big data analysis, data conditioning, software development, and data modeling
Experienced in utilizing web services and third provider data services
Advanced experience with visualizing/presenting data for stakeholders
Experience in statistical and data mining techniques, including generalized linear model/regression, random forest, boosting, trees, and social network analysis.
Equipment Operated: All specific equipment related to Information Technology as well as routine office equipment.
Abilities and Skills: Must be able to perform complicated research, reporting, application and process analysis, and querying of data. Strong attention to detail. Strong organizational and planning skills. Impeccable written and verbal communication skills. Problem Solving, Process Improvement, Project Management, and Reporting.
Physical Effort: Occasional lifting, up to 25 pounds, required. Normal vision and hearing required.
Working Conditions: Work is performed in an office environment with higher and/or longer noise level than average. Weekends, evening hours, overtime and/or overnight travel will occasionally be necessary.