Staff Scientist

Job Description

The Role

We are seeking a highly skilled and motivated Staff Scientist with strong leadership skills to join our Applied Analytics and Insights team at GM. In this role, you will partner with business stakeholders, product managers, and other data science teams to develop AI/ML solutions that create significant business value. You will work on developing and leading new and creative data science solutions aimed at enhancing GM's customer experience and profitability.

What You'll Do

• Collaborate with business stakeholders, product managers, and data science teams to develop actionable, high-impact data analytical models and insights in a variety of core business areas.

• Lead and mentor other scientists to drive high-quality analytical products in a timely manner, ensuring we are solving the right problems, using the right methods and techniques to solve these problems, drawing the right conclusions.

• Direct the working team’s approach balancing the delivery of high quality of work, speed-to-market, and scalability.

• Develop industry leading solutions through appropriate problem framing/scoping, data requirements identification, data exploration, robust model selection and assessment, and model productionization/monitoring.

• Identify opportunities to leverage data and design data science solutions that will support business decision making and create enterprise value.

• Work closely with business stakeholders, data scientists, data engineers, and product managers to ensure consistent progress towards solution development and business adoption/consumption.

• Communicate findings and recommendations to stakeholders in a clear and actionable manner, influencing senior leaders to use data and insights to make data-driven decisions.

• Stay current with the latest advancements in data science, AI, and machine learning technologies, mentoring team member on data science best practices.

Required Qualifications

• 10+ Years of professional experience in the area.
• A Bachelor's degree in computer science, engineering, statistics, mathematics, physics, econometrics, or a related degree
• Master’s degree in computer science, engineering, statistics, mathematics, physics, econometrics, or a related degree

Business Acumen:

• Ability to understand complex business processes, and how business value is created. Based on that knowledge, propose analytic strategies and solutions that challenge and expand the thinking of the working team.

• Ability to create structured problem statements and conceptualize potential solutions from rough client specifications and information.

• Ability to communicate analyses, status, results, and recommendations to business management and executives in business terms.

Technical expertise:

• Expert knowledge and experience in one or more of these areas*: Numerical optimization, econometric modeling and forecasting, machine learning, Bayesian statistics, game theory, agent-based simulation, text analytics, and computer vision / pattern recognition

• Experience with analyzing source system data and data flows and working with structured and unstructured data.

• Experience with manipulating high-volume, high-dimensionality data from varying sources to highlight patterns, anomalies, relationships, and trends.

• Excellent technical knowledge in two or more of the following technology areas:

  • Analytic tools and languages for statistical and machine learning models such as Python (Sci-Kit Learn), Spark, R

  • Deep Learning frameworks and tools such as TensorFlow

  • Cloud based data science platform such as Databricks and Azure

  • Data management and processing using Postgres and Databricks

  • Data visualization with tools such as Power BI and Tableau

  • Application development using Java, Springboot, React, Node, or Angular

Additional Job Description

Preferred Qualifications

• Ph.D. preferred computer science, engineering, statistics, mathematics, physics, econometrics, or equivalent 10+ year’s work experience in related technical or quantitative fields required (*see above technical areas).

• Flexible analytic approach that allows for producing results at varying levels of precision.

• Strong listening and communications skills, with ability to clearly and concisely explain complex problems and technologies to non-expert and executive audiences.

• Evidence of being able to