Data Scientist III

BMC Software

53d•$114,525 - $190,875•Remote

About The Position

BMC is seeking an experienced Data Scientist to join the Intelligent z Optimization & Transformation team (IZOT), specifically the AMI Platform team. This fully remote U.S. role designs and builds enterprise-grade Machine Learning and Generative AI solutions for complex business challenges. The work includes hands-on use of LLMs, RAG architecture, prompt engineering, and agentic AI frameworks, along with defining how these systems are evaluated, optimized, and deployed in production. The position requires delivering validated, reproducible solutions suitable for mission-critical use and collaborating with domain experts and stakeholders. BMC is unable to offer visa sponsorship for this role.

Requirements

At least 6 years of Data Science experience, with proven expertise in Machine Learning and Generative AI.
B.Sc. in Computer Science, Engineering, or a related field.
Experience working with Large Language Models such as OpenAI, Anthropic, Gemini, or Llama, and familiarity with different LLM architectures.
Hands-on experience with prompt engineering, Retrieval Augmented Generation (RAG), LLM evaluation, and AI application development.
Experience designing performance metrics and evaluation frameworks for AI/ML systems.
Familiarity with agentic frameworks and agent-based workflows using LangGraph, LangChain, or CrewAI.
Strong proficiency in writing Python backend APIs using FastAPI, Flask, or similar.
Proficiency in data science libraries such as Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow.
Strong knowledge of statistical analysis, hypothesis testing, data mining, and machine learning techniques.
Experience querying and analyzing data using SQL and modern data platforms.
Proficiency in data exploration and data visualization techniques and tools.
Familiarity with cloud platforms such as OpenShift (OCP) and AWS.
Self-starter with intellectual curiosity; able to self-learn, adapt, and work in a multitasked, dynamic environment.
Excellent communication skills, including the ability to explain complex technical concepts and predictive analytics to non-technical audiences.

Nice To Haves

Experience with LLM evaluation and observability tooling such as Langfuse and OpenTelemetry-based stacks.
Experience with vector databases and embedding models for retrieval and semantic search.
Experience with MLOps practices such as experiment tracking, model registries, and pipelines using MLflow or Kubeflow.
Experience with fine-tuning and open-weight models such as Llama, Mistral, and Qwen.
Experience with Agile methodology and Atlassian products such as Jira and Confluence.

Responsibilities

Design and develop Machine Learning and Generative AI solutions for complex business problems using statistical analysis, data mining, and machine learning techniques.
Apply prompt engineering, RAG, and LLM evaluation in end-to-end AI application development.
Analyze complex problems and situations that require in-depth evaluation of multiple factors.
Collaborate with domain experts to understand business requirements and formulate data-driven solutions.
Deliver solutions that meet enterprise-grade quality standards and are rigorous, validated, reproducible, and ready for mission-critical use.
Define and implement evaluation frameworks for agent accuracy, task completion, reliability, and user satisfaction.
Develop benchmarks, test datasets, and performance metrics for agentic AI systems.
Contribute to AI governance, model validation, and continuous improvement initiatives.
Implement model optimization strategies that account for the constraints and requirements of mainframe environments.
Support packaging and deployment of models and AI solutions into production environments.
Explain complex technical concepts and predictive analytics clearly to technical and non-technical audiences.
Contribute to code reviews, technical documentation, and best practices.