Data Science Expert

16 hours ago

Meerut, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 3,00,00,000
Our organization seeks a seasoned expert in data science to fill the position of Senior Data Scientist. As our primary technical representative for enterprise clients, you will be responsible for developing and implementing tailored AI/ML solutions that drive measurable business outcomes.Key Responsibilities:
  • Serving as the primary point of contact for our enterprise clients, building trusted relationships with stakeholders from technical teams to C-level executives is essential.
  • Designing and architecting end-to-end ML solutions, including predictive models, recommendation systems, and generative AI applications tailored to customer use cases is a key requirement.
  • Leading proof-of-concepts, pilot deployments, and production implementations while ensuring seamless integration with customer systems is crucial.
  • Conducting data assessments, providing ML strategy recommendations, and guiding customers through model lifecycle management is vital.
  • Mentoring customer teams and building internal data science capabilities through training and best practices sharing is essential.
  • Gathering customer feedback to enhance existing solutions and identify new product opportunities is important.
Required Skills and Qualifications:

Education & Experience:

  • Master's in Data Science, Computer Science, Statistics, or a related quantitative field is required.
  • At least 5 years of hands-on data science experience with at least 2 years in customer-facing or consulting roles is necessary.
  • A proven track record delivering ML solutions in production environments is essential.
Technical Skills:
  • Advanced programming skills in Python/R and strong SQL capabilities are required.
  • Deep learning, NLP, traditional ML algorithms, and generative AI/LLMs expertise is necessary.
  • Frameworks such as TensorFlow, PyTorch, scikit-learn, and cloud ML services (AWS/Azure/GCP) are required.
  • MLOps platforms, data visualization tools, and big data technologies are also necessary.

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