- The Global Data Insights and Analytics (GDI&A) Program and Launch Management Analytics team supports Ford s Vehicle Launch Initiatives with analytical solutions to enable corporate targets to improve timing, quality, and cost metrics
- We are looking for a manager to lead a team of data scientists, ML individual contributors, and software engineers in all phases of ongoing and future analytics projects, including problem formulation, data identification, model development, validation, and deployment
- As a member of this dynamic team, you will have the opportunity to work with some of the brightest global subject matter experts in Vehicle Launch, Quality, Warranty, and the Voice of Customer who are transforming the automobile industry
- The candidate should have great independence, exceptional collaboration and leadership skills, and self-discipline to guide original applied research and choose appropriate methodologies to solve related problems
- We are especially excited about candidates with supervisory experience, passion for hands-on work, and a strong technical mindset who demonstrate a passion for developing data science teams and applying state-of-the-art solutions to novel and challenging problems
Basic Qualifications:
- masters degree in Engineering, Data Science, Computer Science, Statistics, Industrial Engineering, or other data-related fields
- 5+ years of domain experience in having developed and applied ML models to improve quality metrics in an OEM
- 5+ years of hands-on experience with application of supervised and unsupervised machine learning techniques in a quality related field
- 5+ years of experience working with a wide range of Data Science and Machine Learning frameworks such as Keras, TensorFlow, PyTorch, Scikit-Learn, XGBoost, etc
- 5+ years of experience in R & Python programming language, and DataRobot
- Demonstrated performance in working on developing analytical models and deploying them in GCP
- Familiarity with SQL, Spark, Hive, and other big data technologies
- Strong drive for results, sense of urgency, and attention to detail
- Strong verbal and written communication skills with the ability to present to cross functional levels of management
- Ability to work in a fast-paced environment with global resources under short response times and changing business needs
Preferred Qualifications:
- PhD in Mechanical/Automobile Engineering, Statistics, Industrial Engineering, or other engineering data-related fields.
- High level understanding of Ford Engineering practices, diverse systems and functions.
- 5+ years of experience with applications of ML models for anomaly detection, document classification, text clustering, topic modeling, sentiment analysis, etc
- 5+ years of experience in applying a wide range of computationally intensive statistical methods, eg bootstrap inference, cross-validation to estimate prediction errors, Markov Chain Monte Carlo, etc to real world problems.
- Familiarity with NLP, Deep Learning, neural network architectures including CNNs, RNNs, Embeddings, Transfer Learning, and Transformers.
- Experience working with NLP/NER systems and frameworks such as NLTK, SpaCy, Gensim, Stanford CoreNLP, OpenNLP, etc
Key Responsibilities:
- Work with the vehicle program teams to apply vehicle launch risk assessment methodologies including program risk score to inflight programs, understand and interpret results, conduct what-if scenarios, and identify and explain risk mitigation strategies
- Continuously assess accuracy of program outcome machine learning models by comparing model results against program outcome data as and when it becomes available
- Improve existing and build new machine learning models to predict program outcomes including unplanned unit loss, 3MIS CPU, QNPS, and MP2 timing slip with new program data and new KPIs
- Work with business partners to update data related to design, launch, quality, and supplier related data towards improving the understanding of the vehicle launch process
Other Responsibilities:
- Lead a group of data scientists, data engineers, and software engineers, through exciting and challenging vehicle launch related projects
- Translate business needs into analytical problems, work hands-on along with the team, judge among candidate ML models, contribute towards best practices in model development, conduct code reviews, research state-of-the art techniques and apply them for the team and business needs.
- Develop and apply analytical solutions to address real-world automotive and Quality challenges
- Initiate and manage cross-functional projects, building relationships with business partners, and influencing decision makers
- Ability to work we'll under limited supervision and use good judgment to know when to update and seek guidance from leadership
- Communicate and present insights to business customers and executives
- Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results
- Explore emerging technologies and analytic solutions for use in quantitative model development
- Develop and sustain a highly performing team
