Simulation Developer Data Scientist

Title:

Duration:

Location:

Interview Mode:

Employer:

Key Responsibilities:

• Design, test, and optimize prompts for

  Generative AI

  applications across multiple business use cases.
• Collaborate with data scientists, platform engineers, and risk teams to ensure compliant and scalable AI model deployment.
• Develop reusable prompt frameworks and documentation for consistent enterprise-wide adoption.
• Evaluate prompt effectiveness using A/B testing, BLEU, ROUGE, and human feedback metrics.
• Integrate AI model APIs (OpenAI, Anthropic, Google Vertex AI, etc.) within enterprise environments.
• Identify and mitigate

  prompt injection risks

  , ensuring adherence to enterprise AI governance and security standards.
• Continuously iterate on model interaction design for clarity, specificity, and contextual accuracy.
• Partner with cross-functional stakeholders to align AI solutions with business objectives and compliance needs.

Required Qualifications:

• 3+ years of experience

  in AI/ML, NLP, or Generative AI systems.
• Hands-on experience with

  LLMs

  (OpenAI, Anthropic, Google Vertex AI, Claude, etc.).
• Strong understanding of

  prompt-response dynamics, tokenization, embeddings

  , and

  semantic similarity

  .
• Proficiency in

  Python

  for automation and API integration.
• Familiarity with

  JSON

  for structured outputs.
• Bachelor’s or Master’s in

  Computer Science, Data Science, Linguistics

  , or related field.
• Excellent communication and analytical skills — ability to bridge technical and business discussions.
• Prior experience in

  regulated industries

  such as

  finance or healthcare

  .

Core Competencies:

Understanding of LLM Behavior:

• Context window management, token processing, and temperature tuning.
• Knowledge of prompt injection vulnerabilities and mitigation strategies.

Prompt Design & Optimization:

• Expertise in

  few-shot

  ,

  zero-shot

  ,

  chain-of-thought

  , and

  role prompting

  .
• Ability to structure prompts for adaptability and precision.

Evaluation & Iteration:

• Experience designing A/B tests and evaluating prompts using

  quantitative (BLEU, ROUGE)

  and

  qualitative

  measures.

Ethics & Responsible AI:

• Awareness of

  bias mitigation

  ,

  fairness

  , and

  safe AI

  deployment practices.

Preferred Qualifications:

• Experience integrating

  Retrieval-Augmented Generation (RAG)

  pipelines.
• Familiarity with

  enterprise AI governance

  and model risk management frameworks.
• Hands-on experience working within

  financial domain

  environments.