AI Engineer

Position Description:

Do you believe data tells the real story We do! Redefining mobility requires quality data metrics and analytics as well as insightful interpreters and analysts. Thats where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions customer needs and the competitive landscape. With our support key decision makers can act in meaningful positive ways. Join us and use your data expertise and analytical skills to drive evidence-based timely decision making. In this position... FCSA (Ford Customer Service Analytics) team part of Sales and Services Data and Analytics (SSDA) department in Ford s Global Data Insight and Analytics (GDI&A) organization is looking for a highly skilled Data Scientist. This role will be a member of RAV (Re-Acquired Vehicle) analytics team supporting all stages of RAV analysis from problem formulation model /analytical framework development evaluation to model deployment to help Ford and FCSD achieve RAV objectives. The FCSA RAV Analytics team applies advanced quantitative methods and systematic econometrics and AI/ML /LLM models to derive insights and solve a wide variety of challenging problems in various area of FCSD: RAV forecast RAV count/spend monitoring/trend study RAV root cause study RAV reduction analytical support/evaluation quality action effectiveness on RAV VOR/uptime early quality detection through analyzing vast amounts of data including RAV quality repair orders repeat visits parts order and supply service warranty claims recall etc. The deep-dive and advanced analytics/quantification analysis supported by this role will be instrumental in supporting FCSDs business objectives and transformation through data-driven decision-making.

Skills Required:

Python GCP SQL Data Analysis

Skills Preferred:

Hybrid Before 09/01 1 day a week. onsite. After 09/01 4 days a week onsite.

Experience Required:

Master s degree in Statistics Data Science Econometrics Engineering Physics or related quantitative field or a combination of education and equivalent work experience 3 years of hands-on experience on a broad range of analytical techniques including forecasting regression and AI/ML/LLM methodologies Strong understanding of machine learning algorithms techniques and frameworks including deep learning neural networks and ensemble methods. 3 years of proficient experience in training evaluating and fine-tuning a variety of machine learning models ensuring optimal performance and reliability 3 years of experience and proficient in programming languages such as Python for data manipulation analysis and model development 3 years of experience in processing large high-dimensional structured and unstructured data including thorough data preprocessing data cleaning and feature engineering to prepare datasets for model training and evaluation

Experience Preferred:

Ph.D. in a quantitative field such as Statistics Data Science Econometrics Engineering Physics or related quantitative field 3 experience GCP (Google Cloud Platform): Vertex AI Big Query GCS (Google Cloud Storage) Google Cloud SQL Looker studio 3 year of post-graduate work experience in auto industry involving complex quantitative analytics and modeling 5 years of work experience with Python and SQL 5 years of work experience in big data manipulation statistical analysis modeling optimization AI/ML/LLM Curious high level of initiative detail-oriented and ability to multi-task Fast learning in theoretical modeling and coding Strong problem formulation and problem solving skills Comfortable working in an environment where problems are not always well-defined

Education Required:

Masters Degree

Education Preferred:

Doctorate

Additional Safety Training/Licensing/Personal Protection Requirements:

Additional Information :

support regional CSM (Customer Satisfaction Model) model framework design/development model maintenance model enhancement and model daily monitoring using Looker Studio. Support RAV annual count forecast taking into consideration of various factors such as brand fuel type launch type new car sales and macro environment in addition to various types of RAV origination. Support RAV Root Cause analysis by studying repair order and warranty claim history to derive and identify potential drivers/trend for RAV Conduct various deep-dive analysis on RAV vehicles to help identify/detect early indication of RAV and uncover/provide insights to business to prevent/reduce RAV Conduct quick turn-around studies to answer frequent/various/urgent business requests by mining managing and exploring a variety of data sources and extracting/deriving insights from structured and unstructured data sets that are often very large and high-dimensional Explore/apply the most relevant quantitative modeling techniques and tools in statistical analysis econometrics operation research/optimization AI/ML/LLM techniques to a variety of real-world business problems within FCSD focusing on improving RAV and service quality Ensure overall quality of the data and solutions throughout the analytics development process Maintain and enhance existing quantitative models supporting FCSD daily decisions Integrate validation result and visualize analysis/prediction result through visualization tools to provide qualitative/quantitative overview Interact/collaborate effectively cross-functionally with a variety of architect project manager DE SE and other data scientists to test data and model pipeline validate pipeline output to ensure successful model launch into production environment to maximize business value delivery Independently and clearly communicating and presenting/interpreting models and analytical results