Job Description



Job Title:

In Global Data, Insight & Analytics (GDI&A), we aspire to navigate Ford Motor Company through the disruptiveness of the information age, harnessing the power of data and artificial intelligence to realize the enterprise’s known goals, reveal hidden opportunities, and achieve data superiority.

The Strategy & Enterprise Analytics team under Connected Vehicle & Enterprise Analytics organization in GDI&A leverages advanced analytics and domain expertise to deliver data analytics models, tools, and services to improve the EV customers’ charging experience, support Ford strategic energy services, meet or exceed regulatory compliance via connected vehicle data, and enable what-if scenario analyses for global cycle plan planning.

We are seeking top-tier Data Scientist who has full-stack of skills in product lifecycle from analytic problem definition, through data gathering, analysis, model and algorithm development, reporting/visualization development, testing, and operational deployment.

Responsibilities:

Acquire deep understanding of the business problems and translate them into appropriate business solutions
Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results
Drive development and delivery of analytic and statistical models using skills such as data acquisition and management, algorithm design, and model development & refinement
Work with business partners using a collaborative, agile approach to develop solutions rapidly that add value and are centered around the user experience.
Act as full stack data scientist to develop mathematical, analytical, optimization and/or AI/ML models to support evidence-based decision making. Ensure overall quality of the data & solutions throughout the analytic development process and support deploying them as end-to-end products on Google Cloud Platform
Examine, interpret and report analytical results in both written reports and in oral presentations to varied audiences


Job Requirements:

Basic Qualifications:

M.S. in Data Science, Computer Science, Electrical Engineering, Applied math, Mechanical Engineering, Industrial Engineering, or related quantitative field
4+ years of experience, including both full-time work and research/academia experience, in programming languages such as Python, R, Scala, Java
3+ years of experience, including both full-time work and research/academia experience, with one or more of the following tools: Data Gathering skills/tools (e.g., BigQuery, SQL, Hadoop, Spark, etc.) and/or Visualization skills/tools (e.g., Qlik Sense, Looker, Streamlit etc.)
3+ years of experience, including both full-time work and research/academia experience, in mathematical programming, data mining, statistical analysis, and/or machine learning
Strong oral, written and interpersonal communication skills
Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations


Preferred Qualifications:

Ph.D. in Data Science, Computer Science, Electrical Engineering, Applied math, Mechanical Engineering, Industrial Engineering, or related quantitative field or 3+ years of industry experience in data science and analysis
Connectivity vehicle, energy management, or EV charging domain experience
5+ years of experience, including both full-time work and research/academia experience, in programming languages such as Python, Scala, Java
5+ years of experience, including both full-time work and research/academia experience, with one or more of the following tools: Data Gathering skills/tools (e.g., BigQuery, SQL, Hadoop, Spark, Teradata, etc.) and/or Visualization skills/tools (e.g., Qlik Sense, Looker, Streamlit etc.)
5+ years of experience, including both full-time work and research/academia experience, in mathematical programming, data mining, statistical analysis, and/or machine learning
1+ year of Google Cloud Platform (GCP) experience, including certifications
Experience in one or more of the following domains: NLP, forecasting algorithms, large scale optimization, and deep learning
Ability to drive results and handle multiple projects within a given timeframe
Well-organized, independent, and ready to work with minimal supervision
Inquisitive, proactive, and interested in learning new tools and techniques
Comfortable working in a fast-paced and innovative environment where problems are not always well-defined
Publications or presentations in recognized journals or conferences