Data Scientist

2 days ago

Chennai Tamil Nadu, India Ford Motor Company Full time

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, NumPy, SciPy, Sklearn, TensorFlow, 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.

**Professional Qualification**:

- 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.

**Technical 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, NumPy, SciPy, Sklearn, TensorFlow, 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.

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