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Your Role
- Develop and implement advanced machine learning models and algorithms to solve complex business problems.
- Design and maintain end-to-end ML pipelines using MLOps best practices for model deployment and monitoring.
- Utilize PySpark for large-scale data processing and transformation.
- Collaborate with data engineers and analysts to ensure data quality, integrity, and accessibility.
- Perform exploratory data analysis, feature engineering, and model optimization.
- Communicate insights and recommendations to stakeholders through clear visualizations and reports.
Your Profile
- Proven experience as a Data Scientist with a strong understanding of statistical modelling and machine learning techniques.
- Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, or similar).
- Proficiency in PySpark and distributed data processing.
- Strong programming skills in Python and familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Knowledge of cloud platforms (AWS, Azure, or GCP) for ML deployment is a plus.
- Excellent problem-solving skills and ability to work in a collaborative environment.
- You will have the opportunity to learn on one of the industry's largest digital learning platforms, with access to 250,000+ courses and numerous certifications.
- We’re committed to ensure that people of all backgrounds feel encouraged and have a sense of belonging at Capgemini. You are valued for who you are, and you can bring your original self to work.
- At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges.
- Capgemini office campuses in India are green and run on 100% renewable electricity. We have installed Solar plants across India locations and ‘Battery Energy Storage Solution’ (BESS) in the Noida and Mumbai campuses. You will have chance to make a difference everyday.
Key Skills
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