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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - USA Remote - **Company:** BMC Software, Inc. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Big Data, BigQuery, Software as a Service, Customer Data Management, Data Presentation, Data Visualization, Python (Programming Language), Machine Learning, Power BI, Cloud Services, Standard Sql, Tableau (Software), Sql Optimization, Large Language Models, Snowflake, Prompt Engineering, Model Validation, Generative AI, Information Technology, HuggingFace, Data Analytics, Looker Analytics, Data Pipelines, Databricks - **Published:** August 26, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88026968/1 ## About the Role * 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 GenAI or AI-enabled analytical workflows is a plus. * Familiarity with BI and visualization tools such as Tableau, Power BI, or Looker Core Skills * 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 ## Description We are seeking a highly skilled Data Scientist with deep experience in B2B SaaS to lead the development of advanced analytics, predictive models, and AI-driven insights that improve business performance and customer outcomes. This role will partner closely with teams across Product, Sales, Marketing, Customer Success, and Data teams to solve high-impact business problems using data science. The ideal candidate brings a strong foundation in statistical modeling, machine learning, experimentation, and business analytics, combined with a practical understanding of key SaaS metrics such as ARR, NRR, churn, retention, expansion, pipeline conversion, customer health, and product adoption. This person must be able to move fluently between technical depth and business context, translating complex data into actionable recommendations that influence strategy and execution., * 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., Success in this role means delivering data science solutions that create measurable business impact. This includes improving customer retention, accelerating growth, increasing forecast accuracy, identifying high-value opportunities, and enabling smarter decisions across the B2B SaaS customer lifecycle. The successful candidate will combine strong technical rigor with business judgment and will help ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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