Senior AI ML Scientist (B2B SaaS Growth)

BMC Software; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

BMC Software in Pune, India, is seeking a highly skilled Data Scientist to lead advanced analytics, predictive modeling, and AI-driven insights that improve business performance and customer outcomes. You will collaborate across Product, Sales, Marketing, Customer Success, and Data teams to translate complex data into actionable recommendations and scalable models.

The ideal candidate has 8+ years in data science in B2B SaaS, mastery of Python and SQL, and hands-on experience with large-scale

Qualifications

• Bachelor’s or Master’s degree in a quantitative field.
• 8+ years of data science & ML experience in B2B SaaS environments.
• Strong expertise in ML, statistical modeling, forecasting, experimentation, and causal analysis.
• Strong proficiency in Python and advanced SQL skills.
• Experience with large-scale business, sales, and product datasets.
• Familiarity with GenAI and AI-enabled analytics workflows is a plus.
• Ability to communicate findings to non-technical audiences and influence decisions.

Responsibilities

• Develop and deploy predictive and prescriptive models across the B2B SaaS lifecycle.
• Build data science solutions for churn, upsell propensity, lead scoring, and segmentation.
• Collaborate with Sales, Operations, Marketing, and Customer Success to drive growth and efficiency.
• Design and analyze experiments, A/B tests, and quasi-experiments to measure impact.
• Apply ML methods to CRM, telemetry, marketing, and financial data.
• Translate business questions into analytical approaches and communicate results to leadership.
• Work with data engineers and BI teams to ensure scalable pipelines and workflows.
• Monitor models, validate assumptions, and improve accuracy and relevance.
• Support self-service insights and reusable data assets for decision-making.
• Document methodologies, assumptions, and business impact clearly.

Skills

Machine Learning

Statistical Modeling

Forecasting

Experimentation

Python

SQL

Data Storytelling

Cross-Functional Collaboration

Education

Bachelor's or Master's in Data Science/Statistics/CS/Math

Tools

Snowflake

Databricks

BigQuery

OpenAI APIs

LangChain

Hugging Face

Job description

Job Summary

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.

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.

Requirements / Experience

• Bachelors or Masters 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

What Success Looks Like

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 embed data science into everyday decision-making across the organization.