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    AI & Data Science Leader - Chennai, India - Ford Motor Company

    Ford Motor Company
    Ford Motor Company Chennai, India

    1 month ago

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    Description

    This is an exciting opportunity to be part of a team that will be instrumental in crafting the future of how we do business, with the commercial customer at the center of everything we do.

    As the Data Science Manager, you should have a strong technical background and demonstrated experience in Data Science and AI/ML.

    You will be responsible for the delivery of analytical models and solutions as well as use your business acumen, knowledge of data, and AI to support key products within Pro Tech that focus on improving customer experience, increasing revenue, and improving efficiency across the business.

    You will be responsible for coaching and providing growth opportunities to direct reports. The Data Science Lead will be able to develop healthy relationships and trust with business stakeholders and peers across Ford Pro-Tech and Ford
    Collaborate with business customers to understand business challenges and develop strategies for solving them using AI/ML and advanced analytics.
    Support technical reviews of analytical methods & AI solutions.
    Support the prioritization of advanced analytic research needed to advance the product's capabilities.
    Hands-on leadership of developing analytical solutions.
    Establish and grow our AI Engineering practice

    Drive AI products and services end-to-end in partnership with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

    Contribute towards advancing the AI Engineering and Data Science discipline in Ford Pro through the Community of Practice, including but not limited to driving data best practices, improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.


    Anchor Role:
    Mandatory qualifications


    Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow.

    Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods.
    Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
    Familiarity with cloud-based data storage and processing technologies for handling large datasets efficiently.
    Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
    Proficiency in programming languages such as Python for data manipulation, analysis, and model development.
    Experience with version control systems like Git for managing code repositories and collaboration.
    Understanding of containerization technologies like Docker for packaging machine learning models and deploying them in production.
    Strong problem-solving skills, analytical thinking, and the ability to communicate complex technical concepts effectively.
    Experience with Gen AI,
    Strong in Software Engineering practices and be able to translate those practices into the AI Engineering world.
    Bachelor's Degree in related field (. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT)
    7+ years of experience of analytical methods and their proper application
    7+ years of experience using AI/ML , data science software (., Python-based tools)

    Our preferred requirements:
    PhD Degree in related field (., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science)
    Expert level of Advanced and Predictive Analytical Methods ., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing,
    Working knowledge of GCP.
    Expertise in open source data science technologies such as Python, R, Spark, SQL.

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