Data Science Manager

This role is responsible for leading a team that collects, analyzes and interprets large volumes of data using software programming and statistical models to detect patterns, trends, and relationships in data sets. The role solves business problems from information derived through systematic analysis of data or statistics, provides research insights and key business drivers to clients and business. The role makes recommendations with trade-offs & implications, using both conventional mechanisms such as reports, dashboards and new, innovative visual approaches and techniques for data storytelling.
**Responsibilities**
- Provides direct and ongoing leadership, updates, and coordination for teams responsible for mining data, and implementing models/predictions to uncover insights and business value.
- Oversees the design, development and optimization of data science processes and programs that enable faster delivery of development activities between environments.
- Validates and approves critical KPIs, reporting frameworks, visualizations, tests, and research to drive business solutions using computational techniques and statistics.
- Manages headcount, deliverables, schedules, and costs for multiple ongoing projects, ensuring that resources are appropriately allocated, and that goals, objectives, timelines, and budgets are met in accordance with program and organizational roadmaps.
- Communicates project status and escalates issues to direct managers, program managers, and internal and external development partners.
- Manages relationships with outsourced partners and suppliers, including setting expectations regarding deliverables, product quality, schedules, and costs.
- Proactively identifies opportunities for process improvement and cost reductions opportunities.
- Provides people-care management for assigned team members, including hiring, setting and monitoring of annual performance plans, coaching, and career development.
- Ensures that proper knowledge and career development tools are in place to support ongoing team member and process development.
- Collaborates with leadership team to understand current business challenges and future business strategy to explore opportunities for data enabled decision making and define a roadmap to achieve the same.
- Drive productivity by evaluating and approving recommended automated processes for large scale data analyses, model development, model validation, and model implementation.
**Education & Experience** Recommended**
- Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or any other related discipline or commensurate work experience.
- Typically has 7-10 years of job-related experience or 5-7 years of management experience, preferably in data analytics, statistical modeling, machine learning, or a related field.
**Knowledge & Skills**
- Knowledge of modern computer science including algorithms, data structures, software architecture. Where applicable, knowledge of cloud and hybrid cloud service architectures and their impacts on development and deployment.
- Understanding of current machine learning algorithms, under which circumstances each is applicable and their pros and cons. Able to compose new model architectures and objective functions. Able to integrate multiple models into systems.
- Knowledge of data processing techniques and data preprocessing requirements for the common machine learning approaches. Knowledge of data collection techniques. Knowledge of data augmentation approaches and their pros and cons.
- Strong leadership skills, including coaching, team building, and conflict resolution.
- Advanced project management skills including time and risk management, resource prioritization, and project structuring.
- Excellent analytical and problem-solving skills.
- Advanced communication skills catered to a wide variety of audiences. (e.g. written, verbal, presentation).
- Advanced multi-tasking and prioritization skills
- Advanced relationship management skills, including partnering and consulting.

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