Managing Director, Automotive Data Science

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

This individual will lead automotive data science development supporting new product development, as well as will lead and enhance our flagship automotive incentive planning model and other capabilities. Our ideal candidates are determined to combine the art and science of data analytics and marketing to help clients address the complex challenges surrounding price, promotion, customer journeys and multi-step purchase decisions. This includes consideration and uptake of new automotive technologies such as electric vehicles, online retailing and connected vehicles.

You will have the freedom to utilize latest technologies to solve challenging problems, create innovative machine learning processes from the ground up, deploy to production, and develop tools for monitoring them

The Impact:

We make data products that solve problems for the auto industry, using a combination of data assets that is unrivaled in the industry.

About the job:

• Lead data science development supporting new product development. Lead enhancements to our flagship incentive planning model
• Implement models that are based on statistics, econometrics, and/or machine learning techniques such as: propensity modeling, logistic regression, choice model, time-series model, panel data model, media mix modeling, multi-touch attribution, Bayesian statistics, structural equations, probability theory, nested logit, clustering algorithms, etc.
• Ensure rigorous quality control relative to industry standards and client-facing acceptance
• Interdisciplinary: drive interaction with multiple teams across the firm to develop or improve analytical capabilities. This includes Consulting, New Product Development, Data, Engineering, etc.
• Recruit, train, hire and inspire the data science team

What we would love to see:

• Demonstrated data science expertise and implementation across a breadth of major industries (5+ years each across 7+ industries) involving consumer behavior, modeling multiple outcomes across a consumer’s journey
• 15+ years of full-time quantitative analytics professional (non-academic) experience and quantified business impact. Used to business timelines for data science in which days, weeks and months dictate the expected pace of incremental improvements
• 10+ years track record of incremental, provable, documented methodological innovation that you spearheaded & implemented across large teams, to differentiate on methodology in competitive environments (e.g., “How did you enhance your models in production – quickly – to address COVID-19? With what data, methods and defense?”)
• 10+ years client-facing and internal senior leadership facing communications responsibilities to convey, defend, and align with technical clients and prospects about your organization’s methodology
• 10+ years successfully leading large (20+) technical cross functional teams, inclusive of data science, but also functions like data engineering, data strategy, data operations, data management
• 10+ years leading teams supporting multiple data science products and capabilities in production. 5+ years leading teams in support of new product development for data science
• 10+ years demonstrated experience successfully mentoring and growing leaders below you in your organization (individual contributors to managers, managers to directors, etc.)
• Demonstrated expertise with data analytics and/or statistical concepts such as: promotion/price, media mix modeling, multivariate regression, logistic regression, time-series modeling, Bayesian statistics, segmentation modeling, machine learning, data mining, simulation, optimization, and/or forecasting
• Fluency in statistical programming software: Python preferred, Spark or R acceptable
• Fluency of database software: SQL preferred
• Experience resolving complex data and analytical issues in creative and effective ways
• Independent professional who can take a vision and implement with limited instruction, with demonstrated experience coordinating activities of technical teams
• Bachelor’s degree (required) with statistics or mathematical background: Econometrics, Statistics, Operations Research, Quantitative Marketing, Finance, Engineering or similar
• Master’s degree in a technical field (e.g. Statistics, Data Science, Economics) a plus. PhD not required
• Ability to manage multiple projects with a large cross-functional team
• Ability and willingness to learn in a fast-paced environment
• Resilient work ethic

The Career Opportunity:

Grow as a data scientist as part of a medium sized team. You will pipeline data, build models, deploy them in the cloud, and build monitoring suites.

The Team / The Business:

The team is an experienced set of creative thinkers who are uncovering new and emerging consumer dynamics in an industry starting to go through rapid disruption