About the Role:
The Data Analytics Expert is responsible for conducting advanced analytics, building predictive models, and applying statistical and machine learning techniques to extract actionable insights that support customer, commercial, revenue, pricing, and growth-related decision-making across the organization.
Role Responsibility:
Use Case Identification:
- Conduct exploratory data analysis and develop advanced analytical use cases in collaboration with commercial, sales, marketing, finance, and customer experience stakeholders.
- Identify opportunities for customer segmentation, churn prediction, lifetime value (CLV), demand forecasting, pricing optimization, and revenue uplift.
- Translate business questions into data science problems, including feature engineering, hypothesis formulation, and model development.
Advanced Analytics Development and Implementation:
- Identify relevant datasets and ensure data readiness for modelling, including cleansing, normalization, and transformation of customer, transaction, pricing, and commercial datasets.
- Assess data quality and completeness; work closely with data engineers to enhance data pipelines and data models.
- Design and develop advanced analytical, ML, and AI models to generate insights across customer behavior, sales performance, product profitability, and commercial efficiency.
- Tune and optimize models for performance, accuracy, robustness, and business relevance.
- Create and maintain clear documentation for models, algorithms, assumptions, limitations, and results.
Market Research and External Analytics
- Conduct market research to assess market size, growth, demand drivers, and competitive landscape.
- Develop market sizing (TAM, SAM, SOM) and demand forecasting models using internal and external data.
- Identify and integrate external data sources to enrich customer and commercial analytics.
- Analyze market trends and scenarios to support strategic planning, pricing, and go-to-market decisions.
Insight Generation development and Decision Support:
- Translate analytical findings into actionable commercial recommendations and communicate insights clearly to non-technical stakeholders.
- Partner with business intelligence and analytics teams to align predictive insights with dashboards, KPIs, and reporting frameworks.
- Support strategic initiatives related to customer growth, retention, pricing strategy, cross-sell/upsell, and commercial optimization.
- Translate market insights into clear recommendations for senior stakeholders.
Qualifications & Experience:
- Bachelor’s in data science, Statistics, Mathematics, Computer Science, or a related quantitative field.
- Having a master’s or PhD degree in a related field is a plus.
- Minimum of 8–10 years of hands-on experience in advanced analytics and data science.
- Strong domain experience in customer analytics, commercial analytics, revenue management, pricing, or growth analytics is required.
- Experience with CRM data and data models (Salesforce CRM preferred)
- Proficiency in SQL (Oracle preferred) for data extraction and transformation.
- Familiarity with working on cloud platforms (e.g., Azure ML) is a plus.