Description

About Trimble Trimble Information Technologies India Pvt. Ltd. is part of Trimble’s global technology ecosystem, delivering innovative solutions that connect the physical and digital worlds. Trimble empowers industries such as construction, agriculture, geospatial, and transportation with data-driven insights, advanced analytics, and cloud-based technologies to improve efficiency, productivity, and sustainability. Job Summary Trimble is seeking a results-driven Data Scientist to support customer growth, product adoption, and revenue optimization initiatives. The role focuses on customer analytics, experimentation, lifecycle optimization, and data-driven decision-making to enhance product-led growth strategies across Trimble’s cloud products and services. Key Responsibilities Customer & Growth Analytics Analyze customer acquisition, activation, and conversion funnels to identify growth opportunities Optimize onboarding, adoption, and upgrade journeys using data-driven insights Support product-led sales strategies through lifecycle and behavioral analysis Experimentation & Statistical Analysis Design, execute, and analyze A/B tests and rapid experiments to improve user engagement and adoption Apply statistical and predictive modeling techniques to interpret customer behavior Measure experiment outcomes and translate findings into actionable recommendations Research & Strategy Identify adoption barriers through user research, feedback analysis, and competitive benchmarking Conduct pricing and monetization analysis to uncover upsell and cross-sell opportunities Support strategic initiatives with market, customer, and product insights Collaboration & Communication Partner with product, marketing, and sales teams to drive data-informed decisions Present insights clearly through dashboards, reports, and executive-ready presentations Document methodologies, experiment designs, and analytical findings Required Qualifications & Experience Bachelor’s or Master’s degree in any discipline (UG/PG) 1–5 years of experience in data science, analytics, or machine learning roles Strong expertise in descriptive and predictive analytics Hands-on experience with A/B testing and experimentation frameworks Proven ability to use analytics to influence marketing, sales, and product decisions Technical Skills Programming & Querying: Python, R, SQL Analytics & Visualization: Excel, Tableau Data Science & ML: Predictive modeling, statistical analysis, machine learning techniques Business Analytics: Funnel analysis, lifecycle metrics, growth experimentation Behavioral & Professional Skills Strong analytical and problem-solving mindset Excellent verbal and written communication skills (English fluency required) Ability to translate complex data insights into business recommendations Strong documentation and presentation skills Collaborative team player with stakeholder management experience Key Skills Data Analysis • Data Science • Machine Learning • Analytics • SQL • Python • Business Strategy • Competitive Analysis • Product Innovation • Predictive Analytics

Role and Responsibilities

• Key Responsibilities Customer & Growth Analytics Analyze customer acquisition, activation, and conversion funnels to identify growth opportunities Optimize onboarding, adoption, and upgrade journeys using data-driven insights Support product-led sales strategies through lifecycle and behavioral analysis Experimentation & Statistical Analysis Design, execute, and analyze A/B tests and rapid experiments to improve user engagement and adoption Apply statistical and predictive modeling techniques to interpret customer behavior Measure experiment outcomes and translate findings into actionable recommendations Research & Strategy Identify adoption barriers through user research, feedback analysis, and competitive benchmarking Conduct pricing and monetization analysis to uncover upsell and cross-sell opportunities Support strategic initiatives with market, customer, and product insights Collaboration & Communication Partner with product, marketing, and sales teams to drive data-informed decisions Present insights clearly through dashboards, reports, and executive-ready presentations Document methodologies, experiment designs, and analytical findings