Lead Data Scientist — Enterprise ML & Predictive Analytics

BMC Software, Inc.; New York (NY); Remote; USD 176,000 - 293,000; Full time

Job summary

BMC Software, Inc. is seeking a Lead Data Scientist to join the AMI team. You will frame business problems as modeling problems, build and validate predictive models, and partner with product and engineering to deploy results that create measurable value.

The role emphasizes statistical rigor, experimental design, and reproducible ML practices for enterprise-grade solutions. Collaboration with AI Engineering and AI Quality is expected, with GenAI features explored when appropriate, while staying

Qualifications

• 12+ years of Data Science experience.
• Degree in Machine Learning, Statistics, Data Science, Physics, or related field / equivalent education and industry experience (Master’s preferred for L3+).
• Proficiency in Python and data science libraries (Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow) appropriate to level.
• Knowledge of statistical analysis, hypothesis testing, experimental design, data mining, and machine learning techniques.
• Experience designing performance metrics and evaluation approaches for predictive ML systems (depth scales with level).
• SQL and modern data platforms; data exploration and visualization.
• Familiarity with cloud platforms such as OpenShift (OCP) and AWS.
• Clear communication; ability to work in a multi-tasked, dynamic environment.
• Evidence of setting a science agenda beyond one technical specialty.
• Major decisions or investments improved by capabilities you established.
• Org/BU-level influence with lasting measurement or modeling impact.

Responsibilities

• Design and develop Machine Learning solutions using statistical analysis, data mining, and classical/modern ML techniques.
• Build, train, validate, and iterate predictive models (classification, regression, ranking, forecasting, anomaly detection, clustering) against clear business outcomes.
• Perform feature engineering, exploratory analysis, and experiment design to improve model quality and decision usefulness.
• Collaborate with domain experts to understand business requirements and formulate data-driven solutions.
• Define offline and online metrics, holdout strategies, and monitoring signals for model performance and drift.
• Deliver models to enterprise-grade quality: rigorous, validated, reproducible, and ready for mission-critical use.
• Support packaging and deployment of models into production with engineering partners; maintain clear handoffs.
• Partner with AI Engineering and AI Quality when classical models or predictive signals feed GenAI / agentic workflows.
• Explain complex technical concepts and predictive analytics clearly to technical and non-technical audiences.
• Set the science agenda for a product area or organization (what to measure, model, and invest in).
• Make consequential tradeoffs among modeling approaches, data investments, and partner capacity.
• Build durable measurement/modeling capabilities that improve major decisions over time.
• Represent DS rigor with senior product, engineering, and business stakeholders.

Skills

Data Science

Python

Statistical Modeling

Machine Learning

Experiment Design

SQL

Cloud Platforms

Communication

Cross-functional Leadership

Decision Making

Product Collaboration

Education

ML/Statistics/Data Science degree

Master’s degree preferred

Equivalent education/experience

Tools

Pandas

NumPy

scikit-learn

PyTorch

TensorFlow

OpenShift

AWS

MLflow

Kubeflow

Jira

Confluence

Job description

BMC Software, Inc. is seeking a Lead Data Scientist to join the AMI team. You will frame business problems as modeling problems, build and validate predictive models, and partner with product and engineering to deploy results that create measurable value.

The role emphasizes statistical rigor, experimental design, and reproducible ML practices for enterprise-grade solutions. Collaboration with AI Engineering and AI Quality is expected, with GenAI features explored when appropriate, while staying