Data Scientist

As a Data Scientist, you will be part of a high performing team working on exciting opportunities in AI/ML within Ford Credit. We are looking for a seasoned Data Scientist with proven expertise in implementing Machine Learning/Optimization solutions with familiarity in Generative AI and a good grasp of Statistics.

• Develop Machine Learning (Supervised/Unsupervised learning), Neural Networks (ANN, CNN, RNN, LSTM, Decision tree, Encoder, Decoder), Natural Language Processing, Generative AI (LLMs, Lang Chain, RAG, Vector Database)
• Hands‑on Expertise in Python programming (OOPs concepts), SQL (relational/non‑relational databases), experience in handling various data science libraries (Pandas, Num Py, Sci Py, Sklearn, Tensor Flow, Keras, Pytorch, etc.) would be a necessary requirement.
• Exposure to Cloud technologies (e.g., Google Cloud/AWS/Azure), including executing Machine Learning algorithms on Cloud is necessary.
• Exposure to Generative AI technologies.
• Ability to scope the problem statement, data preparation, training and making the AI/ML model production ready.
• Work with business partners to understand the problem statement, translate the same into analytical problem.
• Ability to manipulate structured and unstructured data.
• Develop, test and improve existing machine learning models.
• Analyse large and complex data sets to derive valuable insights.
• Research and implement best practices to enhance existing machine learning infrastructure. Develop prototypes for future exploration.
• Design and evaluate approaches for handling large volume of real data streams.
• Ability to determine appropriate analytical methods to be used.

Collaborate with data engineers, solutions architects, application engineers, and product teams across time zones to develop data and model pipelines.

• Potential candidates should possess 3 to 7 years of working experience as a Data Scientist.
• BE/MSc/ MTech /ME/PhD (Computer Science/Maths, Statistics).
• Possess a strong analytical mindset and be very comfortable with data.
• Experience with handling both relational and non‑relational data.
• Hands‑on with analytics methods (descriptive/predictive/prescriptive), Statistical Analysis, Probability and Data Visualization tools (Python‑Matplotlib, Seaborn).
• Background of Computer Science with excellent Data Science working experience.

• Develop Machine Learning (Supervised/Unsupervised learning), Neural Networks (ANN, CNN, RNN, LSTM, Decision tree, Encoder, Decoder), Natural Language Processing, Generative AI (LLMs, Lang Chain, RAG, Vector Database).
• Hands‑on Expertise in Python programming (OOPs concepts), SQL (relational/non‑relational databases), experience in handling various data science libraries (Pandas, Num Py, Sci Py, Sklearn, Tensor Flow, Keras, Pytorch, etc.) would be a necessary requirement.
• Exposure to Cloud technologies (e.g., Google Cloud/AWS/Azure), including executing Machine Learning algorithms on Cloud is necessary.
• Exposure to Generative AI technologies.