Job Title: Data Scientist Location: Bengaluru Experience Required: 5+ years About the Role: Analytics Saves at Work is looking for an experienced Data Scientist to lead data-driven innovation and marketing analytics. You will apply machine learning, predictive modelling, and advanced analytics to measure campaign performance, design attribution models, and drive marketing ROI. The role requires strong technical skills, business acumen, and the ability to translate insights into actionable strategies for stakeholders. Key Responsibilities: Campaign Performance Measurement : Develop and maintain a comprehensive framework to measure omni-channel campaign performance, providing actionable insights and recommendations to optimise campaign ROI and inform future marketing strategies. Marketing Attribution Modelling : Design and implement advanced marketing attribution models to quantify the impact of marketing efforts on business growth, sales funnel development, and customer acquisition. Predictive Analytics : Collaborate with marketers to develop business hypotheses and apply predictive analytics, statistical techniques, and machine learning algorithms to drive strategic decision-making and campaign optimisation. A/B Testing and Experimentation : Design, execute, and analyse A/B tests to determine cause-and-effect relationships between marketing actions and business outcomes, informing data-driven decision-making. Data Integration and Automation : Develop and maintain automated reporting solutions, including dashboards and data visualizations, to deliver timely insights and performance metrics to stakeholders. Stakeholder Collaboration : Partner with cross-functional teams, including marketing, sales, and data analytics, to drive process efficiencies, scale analytics capabilities, and communicate marketing program performance. Buyer Journey and Persona Development : Provide data-driven insights and guidance on the development of buyer journeys, personas, and content consumption strategies based on campaign performance analysis. Requirements: Master's or Advanced Degree : In a quantitative field such as Statistics, Engineering, Sciences, or equivalent practical experience. 5+ Years of Analytical Experience : Including experience in statistical modeling, A/B testing, Python, and SQL. 5+ Years of Experience with Adobe AEP, RTCDP, CJA, and Marketo Measure : Demonstrated expertise in using these tools to analyze and optimize marketing campaigns. 5+ Years of Experience with BI Tools : Such as Tableau, ThoughtSpot, Qliksense, Looker, etc. Cloud Platform Experience : Databricks, AWS Redshift, Azure, Snowflake, etc. Industry Experience : Healthcare, insurance, or financial services experience preferred. B2B Marketing Knowledge : Familiarity with B2B marketing principles and practices.
Role & responsibilities AI & Analytics Delivery • Lead business-driven analytics and AI initiatives that support Finance priorities. • Review and assess new AI ideas, run feasibility reviews, and lead proof-of-concept work in controlled sandbox environments to confirm value and ROI. • After validation, work with technology teams for implementation and production rollout. • Design and deliver BI and reporting solutions end-to-end, including dashboards, KPIs, and self-service reporting, with tech support as needed. • Drive modernization and simplification of Finance reporting to improve speed, accuracy, and transparency. • Use enterprise tools such as Microsoft Fabric, Databricks, Denodo, and Power BI to deliver insights that support forecasting, allocations, planning, and performance management. Cross-Pillar Collaboration • Partner with the Data Strategy (VISTA) and Process Reengineering (POET) teams to deliver integrated data, process, and analytics solutions. • Work with GCC Finance, Technology, Platform Engineering, AI CoE, HUB, and Enterprise Architecture to ensure scalable and compliant delivery. • Maintain strong cross collaboration between teams for alignment and reuse of analytics and AI assets. Governance & Value Realization • Apply standards for responsible AI use, documentation, and governance. • Track and report outcomes such as shorter cycle times, higher forecast accuracy, and reduced manual effort. • Protect sensitive finance data and uphold enterprise privacy and control requirements. Leadership & Capability Building • Manage and coach a 57-member team of data scientists, BI developers, and automation specialists. • Build local capability in analytics and automation through training and mentorship. • Promote a culture of innovation and continuous improvement across the Finance Data Office. Qualification & Experience •13-16 years in analytics, data science, or business intelligence with at least 5 years in a leadership or lead role. • Experience delivering analytics or automation initiatives for Finance or FP&A functions. • Knowledge of finance data domains such as general ledger, allocations, forecasting, and planning. • Strong skills in tools like Power BI, Databricks, Microsoft Fabric, and Denodo. • Familiarity with AI/ML frameworks (Python, TensorFlow, Azure ML) and emerging GenAI and automation tools. • Experience managing teams across geographies and collaborating across time zones. • Certifications such as Azure AI Engineer or Data Science Professional are a plus. • Strong communication and stakeholder management skills.
,; About the Role We are building a founding AI & Analytics team within our client's Finance team as part of the Finance Data Office in Hyderabad. This is not a research lab, its a hands-on team that will define how Finance operates in the AI era. Our goal is simple: use AI and data to make Finance faster, smarter, and more efficient. If you enjoy solving real business problems, building end-to-end AI solutions, and creating things that actually get used, this is the team to join. What Youll Work On Youll tackle some of Finance’s most important challenges — the ones that currently require manual effort, repeated checks, or slow hand-offs. Your work may include: Using LLMs, small LMs, GenAI, and NLP to understand complex contracts, guarantees, and rebate terms Building AI agents and automated workflows that simplify multi-step Finance processes Creating smarter forecasting and scenario-planning models that help teams make better decisions Automating business processes to speed up close activities and reduce manual work Designing solutions that reconcile data across systems and flag mismatches before they become issues Building reliable data pipelines that power AI models, reporting, and real-time insights In short: you will make AI real inside Finance, embedded in daily operations, not sitting on the side as an experiment. Who We’re Looking For We’re not hiring for rigid job titles. We’re looking for builders , people who can understand a business problem, explore the data, and create a working solution. You might be a great fit if you have: Core Technical Skills Strong hands-on experience with Python, machine learning, and AI engineering Experience with GenAI, LLMs, small language models, RAG, and agentic AI Confidence designing and tuning NLP and predictive models Ability to build and manage data workflows on platforms like Databricks, or similar Strong prompt engineering fundamentals Problem-Solving + Business Skills Ability to translate business needs into technical solutions (e.g., “How can we improve cash forecasting accuracy, not just build another model?”) Comfort working with Finance datasets or ERP-related data Curiosity, adaptability, and the drive to build new solutions without a playbook Experience partnering with engineering teams and AI CoEs to productize models Ways of Working Comfortable starting small, iterating quickly, and improving based on feedback Able to collaborate directly with global Finance stakeholders Experience working in global environments and empathy for end users We value mindset as much as skillset, we want people who enjoy figuring things out and want to see their work make an impact. Why This Role Is Exciting This is a rare opportunity to build AI capabilities from the ground up inside a large, global organization. You’ll get: The freedom to build and experiment The ability to see your work used by real Finance teams The chance to shape how Finance operates in the future Visibility and impact across multiple Finance functions You won’t be executing someone else’s roadmap, you’ll help create it. Qualifications & Experience 5-8 years in analytics, data science, or business intelligence with at least 5 years in a leadership or lead role. • Experience delivering analytics or automation initiatives for Finance or FP&A functions. • Knowledge of finance data domains such as general ledger, allocations, forecasting, and planning. • Strong skills in tools like Power BI, Databricks, Microsoft Fabric, and Denodo. • Familiarity with AI/ML frameworks (Python, TensorFlow, Azure ML) and emerging GenAI and automation tools. • Certifications such as Azure AI Engineer or Data Science Professional are a plus. • Strong communication and stakeholder management skills.