Chief AI Architect

7 days ago

Aurangabad, Maharashtra, India beBeeDataScientist Full time ₹ 1,37,00,000 - ₹ 2,24,60,000
Lead Enterprise AI/ML Solutions

As a senior data scientist, you will be the primary technical expert for enterprise customers. This role combines deep machine learning expertise with exceptional client relationship skills to design, implement, and deliver tailored AI/ML solutions that drive measurable business outcomes.

Key Responsibilities:

  • Serve as the primary technical contact for enterprise customers, building trusted relationships with stakeholders from technical teams to C-level executives.
  • Architect end-to-end ML solutions, including predictive models, recommendation systems, and generative AI applications tailored to customer use cases.
  • Lead proof-of-concepts, pilot deployments, and production implementations while ensuring seamless integration with customer systems.
  • Conduct data assessments, provide ML strategy recommendations, and guide customers through model lifecycle management.
  • Mentor customer teams and build internal data science capabilities through training and best practices sharing.
  • Gather customer feedback to enhance existing solutions and identify new product opportunities.
Required Qualifications

Qualifications:

  • Master's in Data Science, Computer Science, Statistics, or a related quantitative field.
  • 5+ years hands-on data science experience with 2+ years in customer-facing or consulting roles.
  • Proven track record delivering ML solutions in production environments.
Technical Skills

Skills:

  • Programming: Advanced Python/R, strong SQL capabilities.
  • Machine Learning Expertise: Deep learning, NLP, traditional ML algorithms, and generative AI/LLMs.
  • Frameworks: TensorFlow, PyTorch, scikit-learn, cloud ML services (AWS/Azure/GCP).
  • Tools: MLOps platforms, data visualization tools, big data technologies.

Business Acumen:

  • Exceptional communication and presentation abilities for technical and non-technical audiences.
  • Strong project management and stakeholder relationship skills.
  • Customer-centric problem-solving mindset.
  • Ability to translate business requirements into technical solutions.

Success Metrics:

  • Customer satisfaction and retention rates.
  • Successful ML solution deployments from concept to production.
  • Revenue growth within assigned accounts.
  • Effective knowledge transfer and capability building.

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