Manager, Data Science and Engineering, Service

This role works to support the budgeting and operational needs of the Service organization. This will include taking business requirements from various stake holders and leaders across the Service, Finance and Strategy organizations, developing machine learning and statistical models for them, testing for best fit and leading the team to deploy the model for consecutive use by the stakeholders. This role will also require excellent communication skills and the ability to present technical solutions to non-technical stakeholders in a clear and concise manner. The role will also take the lead in organizing and building a team of Data Scientist and Engineers to support the global service field operations teams expansion and budgeting objectives.

Responsibilities

• Manage a team of data professionals working across a variety of areas and data responsibilities and grow the team by hiring and finding great candidates, establishing, and maintaining team culture.
• Ensure high technical standards by instituting processes (architecture and design reviews, testing, and documentation) and culture (engineering excellence).
• Collaborate with internal organizations to identify, frame, develop, and execute analytics projects successfully.
• Develop the team from the ground up, setting the strategy, objectives and key results, and defining clear roles and responsibilities. Play an active role in our team’s leadership, taking initiative to execute on our mission, prioritize work, make tradeoffs, manage conflicts, and constantly push the team to grow and evolve.
• Contribute and add to the team’s code base and technical design by leveraging state of the art machine learning techniques for a variety of problems across the company
• Lead packaging and deployment of data models to the broader organization and presentation on new tools to the appropriate stakeholders.
• Partner with senior leaders to create a resource planning strategy and roadmap, inclusive of timelines
• Perform research and analysis in support of operations

Qualifications

• Minimum 7 years of experience of data science and machine learning experience.
• Minimum 3 years of experience successfully leading data and/or decision science technical teams
• Demonstrated expertise in one or more of the following: digital services, aftersales, revenue management, sales & marketing, product development, portfolio planning, quality, supply chain, purchasing, or market research
• Strong project management skills with demonstrated successes delivering in an agile manner
• Strong communicator, with ability to partner at the most senior levels of the finance organization and experience presenting and build relationships with internal stakeholders
• Ability to train, mentor, and evaluate the technical capabilities of other
• Ability to prioritize and manage multiple tasks and projects at once without sacrificing quality
• Ability to evaluate the big picture and solve business problems rather than focusing solely on metric
• Experience programming with Python, Scala, Java or C/C
• Knowledge of underlying mathematical foundations of statistics and machine learning. Hands on experience and in-depth knowledge of deep learning, CNNs, NLP, signal processing, optimization, and other advanced analytics techniques is highly preferred.
• Experience with cloud technologies and tech stack including but not limited to big data technologies (Spark, database systems, ETL, etc.), Kubernetes, Airflow, Kubeflow, MLFlow, or any other data science/ML pipeline or platforms.

Education and Training

• Bachelor's degree in a quantitative discipline or equivalent practical experience
• Masters or PhD in computer science, mathematics, engineering preferred.
• Previous experience in Management consulting firm, Start up, Automotive OEM or Aftermarket or equivalent experience preferred