Data Scientist

Role Overview

The Data Scientist – Sales Growth & Market Insights will play a key role in transforming data into actionable strategies that improve sales performance, customer engagement, and market share. This individual will use advanced analytics, statistical modeling, and machine learning to identify trends, forecast demand, and optimize sales initiatives across our diverse product portfolio.

Key Responsibilities

1. Revenue Optimization & Cross-Selling

• Analyze historical market sales data across thousands of SKUs (Stock Keeping Units), internal sales data, pricing trends, customer behavior, and market data to identify
• Opportunities for revenue growth at customer level
• "White Space" opportunities (e.g., customers who buy containers but not lids).
• Build Recommender Systems to suggest next-best-action products for Account Managers to pitch to existing clients.

2. Churn Prediction & Retention

• Develop predictive models to identify B2B clients showing early signs of churn or volume reduction.
• Create automated alerts for the sales team when a client’s purchasing pattern deviates from the norm (anomaly detection).

3. Pricing Strategy

• Analyze pricing elasticity across different regions and industries to recommend margin improvements based on competitor insights.
• Assist in modeling the impact of raw material cost fluctuations (resin indices) on product pricing and customer demand.

4. Forecasting & Market Intelligence

• Utilize time-series forecasting to predict product demand, sales performance and to help us align sales targets with production capacity.
• Segment our customer base (clustering) to tailor marketing campaigns and sales approaches for specific verticals (e.g., Medical vs. Food Service).

4. Other responsibilities

• Develop dashboards and data visualization tools to support decision-making for senior management.
• Integrate data from various sources (CRM, ERP, supply chain, market intelligence platforms) to create a holistic view of commercial performance.
• Present findings and recommendations in clear, actionable formats to both technical and non-technical stakeholders.
• Support business planning and performance reviews through advanced analytics and scenario modeling.

Qualifications & Experience

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• 3–5+ years of experience in a data analytics or data science role, preferably in manufacturing, FMCG, or packaging sectors.
• Proven experience with data analysis tools and programming languages (Python, R, SQL) and in leveraging Artificial Intelligence (AI) and Generative AI (GenAI) technologies to drive business outcomes.
• Hands-on expertise with AI-driven tools, frameworks, and platforms for data analysis.
• Ability to identify and implement GenAI use cases across strategy, operations, and client solutions.
• Strong skills in data visualization (Power BI, Tableau, or equivalent).
• Familiarity with CRM systems (e.g., Salesforce) and ERP platforms (e.g., SAP) is an asset.
• Experience with predictive modeling, clustering (K-Means), and regression techniques.
• Excellent analytical thinking, business acumen, and communication skills.

Key Competencies

• Strong commercial mindset with an ability to translate data insights into business opportunities.
• High attention to detail and data accuracy.
• Collaborative and able to work cross-functionally across sales, marketing, and operations.
• Curious, proactive, and passionate about driving measurable business results through analytics.