01Key Responsibilities
Strategic & Technical Leadership: Lead business engagement, apply and refine methodologies to deliver analytical solutions that help data driven decision making to reduce cost, improve quality and deliver value across Ford Enterprise.
Data Improvement & Integration: Collaborate with business partners, GDI&A functional teams and Centers of Excellence to improve data quality and integrate data from diverse sources.
Hands-on Expertise: Build, improve, and deploy Machine Learning & AI models to provide descriptive, predictive and prescriptive analytics.
Team Leadership & Mentorship: Lead, mentor, and develop a high-performing team, fostering best practices in software development and data science.
Technology Strategy: Develop and implement a roadmap for adopting and integrating new technologies (e.g., GCP).
Cross-functional Collaboration: Work effectively with various teams and stakeholders to achieve business objectives
Required:
Master's degree (PhD preferred) in Engineering, Data Science, Computer Science, Statistics, Industrial Engineering, or a related field.
5+ years of hands-on experience applying supervised and unsupervised machine learning and AI/ML techniques field (OEM experience preferred).
5+ years of leading a team of cross-functional technical experts.
Proficiency in R and Python, along with experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn, XGBoost).
Experience with GCP and data related technologies (SQL, Spark, Hive).
Strong technical & people leadership, communication, and collaboration skills.
Experience working with Agile methodologies.
Strong experience with Java/AngularJS/ReactJS.
Preferred:
Experience with NLP, deep learning, neural network architectures, computer vision, reliability, survival analysis and anomaly detection techniques.
Familiarity with computationally intensive statistical methods, Software development life cycle, Agile, Jira, system architecture principles, PDO processes and software craftmanship.
Google Digital Leader certification. .
