Analytics Manager

The Global Data Insights and Analytics (GDI&A) Sales and Services Data and Analytics team supports Ford’s Sales and Service Initiatives with analytical solutions to generate business value for the company. We are looking for a versatile professional who will be a mix of individual contributor and manager, and work with 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 (traditional statistical models, Machine learning based models, NLP/LLM/GenAI based models), 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 that are transforming the automobile industry. The candidate should have great independence, exceptional collaboration, and leadership skills, and self-discipline to guide original applied work and choose appropriate methodologies to solve related problems in areas including yield management, sales forecast, web analytics, and customer analytics.
 

Key Responsibilities:

• Liaise with the GDI&A Sales and Service Data and Analytics Operations Committee (OCM) to understand, scope, and translate business problems to analytically tractable frameworks
• Use advanced data science techniques to assemble and connect data across diverse sources, build machine learning models from first-principles or using ML platforms such as DataRobot
• Solve problems using advanced AI techniques including GenAI methods by designing NLP/LLM/GenAI applications/products with robust coding practice
• Deploy REST APIs or a minimalistic UI for ML and NLP applications using Docker and Kubernetes tools
• Showcase ML/NLP/LLM/GenAI applications to users through web frameworks (Angular, Dash, Plotly, Streamlit, etc.) in order to generate business value
• Built modular AI/ML products that could be consumed at scale
• Develop and sustain a high performing team 

Basic Qualifications: 

• Master’s degree in Engineering, Data Science, Computer Science, Statistics, Industrial Engineering or other data-related fields
• 5+ years of hands-on experience with application of supervised and unsupervised machine learning techniques in sales and service related domain
• Domain experience in having developed and applied ML models to improve sales and service metrics in an OEM
• 5+ years of experience working with a wide range of Data Science and Machine Learning frameworks including Keras, TensorFlow, PyTorch, and Scikit-Learn.
• 5+ years of experience in R, Python programming language, and DataRobot
• Demonstrated performance in 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
• Experience in LLM models like PaLM, GPT4, Mistral (open-source models)
• Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring. 
• Expertise in handling large scale structured and unstructured data. 

Preferred Qualifications: 

• PhD in Computer Science, Statistics, Industrial Engineering, or other data-related fields.
• 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, e.g. 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.