Note: The job is a remote job and is open to candidates in USA. BMC Software is an enterprise software company that connects people, systems, and data to help organizations accelerate business value. The Senior Data Scientist will lead advanced analytics, predictive modeling, and AI-driven insight initiatives for B2B SaaS, partnering with cross-functional teams to improve growth, retention, forecasting, and customer outcomes.
Responsibilities
- Develop and deploy predictive and prescriptive models to solve critical business problems across the B2B SaaS lifecycle
- Build data science solutions for use cases such as customer churn prediction, upsell propensity, lead scoring, pipeline forecasting, product adoption, customer segmentation, pricing optimization, and customer health scoring
- Partner with Sales, Operations, Marketing, and Customer Success teams to identify opportunities where data science can improve growth, retention, and operational efficiency
- Design and analyze experiments, A/B tests, and quasi-experimental studies to measure the impact of product, marketing, and sales initiatives
- Apply statistical methods and machine learning techniques to large, complex datasets from CRM, product telemetry, marketing, support, finance, and customer systems
- Translate business questions into structured analytical approaches and communicate findings clearly to executive and cross-functional stakeholders
- Collaborate with data engineers, analytics engineers, BI teams, and architects to ensure scalable data pipelines and production-ready modeling workflows
- Monitor model performance, validate assumptions, and continuously improve model accuracy, explainability, and business relevance
- Support the development of self-service insights, reusable data science assets, and scalable frameworks for decision-making
- Document methodologies, assumptions, and business impact in a clear and reproducible manner
Skills
- • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics or a related quantitative field
- • 8+ years of experience in data science & machine learning, with significant experience in B2B SaaS environments
- • Strong expertise in machine learning, statistical modeling, forecasting, experimentation, and causal analysis
- • Strong proficiency in Python and advanced SQL skills
- • Experience working with large-scale business, sales, and product datasets, including CRM, telemetry, subscription, and customer data
- • Deep understanding of B2B SaaS business models and core metrics such as ARR, MRR, churn, retention, expansion, NRR, CAC, LTV, conversion, and product usage/adoption
- • Hands-on experience with large language models (LLMs) and modern AI frameworks such as OpenAI APIs, LangChain, LlamaIndex, Hugging Face, or similar tools
- • Familiarity with RAG, prompt engineering, model evaluation, guardrails, and responsible AI practices for enterprise-ready AI solutions
- • Experience with cloud data platforms such as Snowflake, Databricks, or BigQuery
- • Experience in subscription analytics, revenue analytics, product-led growth, or customer lifecycle modeling
- • Experience building models that support GTM, Product, or Customer Success decision-making
- • Strong ability to communicate technical findings to non-technical audiences and influence business decisions
- • Experience working cross-functionally in fast-paced, matrixed environments
- • Familiarity with BI and visualization tools such as Tableau, Power BI, or Looker
- Machine Learning
- Statistical Modeling
- Forecasting
- Experimentation and A/B Testing
- Customer Churn and Retention Analytics
- Product Adoption Analytics
- Revenue and Growth Analytics
- Segmentation and Propensity Modeling
- Python
- SQL
- Applied AI / Generative AI
- Large Language Models (LLMs) / Retrieval-Augmented Generation (RAG)
- Data Storytelling
- Cross-Functional Business Partnership
- • Familiarity with GenAI or AI-enabled analytical workflows is a plus
Benefits
- Remote work in the United States
Company Overview
Company H1B Sponsorship