Data Scientist

Role Overview:

Key Responsibilities:Operationalize

• Partner with

  Product Managers

  to understand customer requirements,

  design prototypes, and deploy solutions to production

  .

• Design, build, harden, and maintain

  the core infrastructure supporting the

  ML platform and lifecycle

  .
• Define and contribute to the

  technology strategy, roadmap, and priorities

  for AI/ML initiatives.
• Automate every aspect of the

  ML infrastructure

  to

  minimize human intervention

  and improve efficiency.
• Encourage and

  implement best practices

  in

  data engineering and software development

  .
• Write

  high-quality, production-grade code

  that aligns with company standards and contribute to

  new standardization efforts

  .
• Implement

  automated testing

  to ensure reliability and correctness of ML models and infrastructure.

Review and mentor

• Actively participate in

  technical communities-of-practice

  and

  continuing education programs

  to advance personal and organizational growth.
• Facilitate

  problem diagnosis and resolution

  across

  technical and functional

  areas.

Required Skills & Competencies:8+ years

• Expertise in

  designing, coding, and scripting

  to develop

  real-world AI/ML solutions

  .
• Strong programming skills in

  Python, Java, or Scala

  with hands-on experience in

  ML frameworks.

• Experience with

  ML model deployment, MLOps, and automation

  .
• Proficiency in

  cloud-based ML solutions.

• Knowledge of

  data pipeline orchestration tools.

• Strong background in

  data engineering concepts.

• Experience working with

  containerization.

• Strong analytical and problem-solving skills with a

  collaborative mindset

  .
• Excellent

  communication and leadership skills

  with the ability to

  mentor and guide

  junior engineers.