Lead Data Scientist Specialist

3 days ago


Hyderabad, Telangana, India Foundation AI Full time
Job Title: Lead Data Scientist

Foundation AI is seeking an experienced Data Science Lead with expertise in Generative AI and LLMs to play a crucial role in developing and implementing cutting-edge generative models and algorithms.

You will collaborate with a multidisciplinary team of researchers, engineers, and data scientists to explore innovative applications of NLP and Generative AI across various domains. The ideal candidate will have a strong background in deep learning, generative models, and computer vision.

The salary for this position is approximately ₹1,200,000 - ₹2,000,000 per annum.

About Us

Our company automates document-dependent workflows according to your rules. We profile matches, classify, and save each document to your DMS. Read more about us at www.foundationai.com

Responsibilities
  • Lead the end-to-end development of Machine Learning / Deep Learning models, including data preprocessing, feature engineering, model training, and performance evaluation.
  • Oversee the entire data science lifecycle, ensuring models are properly developed, validated, and deployed in all environments.
  • Collaborate with stakeholders to define data science strategies that align with business objectives and identify new opportunities where data science can add value.
  • Design and plan solutions, select appropriate algorithms, and manage technical resources to solve business problems effectively.
  • Mentor junior team members, providing technical guidance and supporting their professional development.
  • Communicate findings and recommendations to stakeholders in a clear and actionable manner.
  • Work closely with cross-functional teams, such as product, engineering, and business, to align data science projects with company goals.
  • Build and foster a collaborative team culture, ensuring best practices are followed and team members are effectively leveraging resources.
  • Ensure data privacy and compliance with regulations like HIPAA.
  • Implement and monitor data quality standards, model fairness, and interpretability, ensuring ethical practices in data use and modeling.
  • Develop key performance indicators (KPIs) for data science projects and regularly evaluate model performance.


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