Data Science Analyst

We bring the world's latest technological products and solutions to our customers, helping them maximize the return on their technology investment by skillfully integrating innovative business solutions, advanced technology and complex system infrastructures. Advanced Analytics Manage the end‑to‑end development of data science projects, translating complex business questions into advanced analytical solutions. Lead the process from identifying new opportunities to delivering insights that drive strategic business outcomes. Model Development and Optimization Develop and deploy predictive and analytical models to support key business functions such as demand planning, cost saving, and revenue growth, with an emphasis on practical application and business impact. Data‑Driven Insight Generation Design and implement solutions for analyzing both structured and unstructured data sources, such as customer feedback and sales data, to uncover actionable business insights and drive strategic outcomes across the region. Data Engineering and Quality Assurance Data Pipeline Development: Perform or oversee data engineering tasks to build, maintain, and optimize robust data pipelines and ETL processes. Data Preparation: Oversee and perform data cleansing, normalization, and validation activities to ensure the accuracy, consistency, and reliability of data. Quality Monitoring: Establish and enforce data quality standards and processes, implementing monitoring and reporting to ensure data integrity across all projects. Project and Change Management Manage analytics projects from discovery to deployment, ensuring timelines and business requirements are met. Vendor Collaboration Evaluate, select, and manage relationships with external data partners and analytics vendors to complement internal capabilities. Stakeholder Management Serve as a key liaison between market teams, regional functions, and global technology partners to ensure project alignment and buy‑in. Strategic Communication & Documentation Effective Communication: Transform complex technical findings and data‑driven recommendations into compelling data visualizations and narratives. Present these strategic insights with clarity and confidence to technical and non‑technical senior stakeholders to influence decision‑making and drive organizational priorities. Strategic Recommendations: Develop and advocate for data‑informed strategic recommendations to drive organizational priorities and decision‑making. Market Playbook Creation: Document methodologies, key findings, and best practices to build reproducible playbooks that empower local market teams to replicate successful analytics initiatives. Qualifications Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, Computer Science, or Business Analytics. 6+ years of experience in a data science or analytics management role, preferably in the multinational food and beverage, retail, or FMCG industry. Deep expertise in building and deploying predictive and analytical models, especially on demand forecasting and sales prediction. Proficiency in data analysis and programming languages (e.g., Python, SQL) and hands‑on experience with ETL and data cleansing processes. Experience with ETL tools such as Alteryx, Azure Synapse, Azure Data Factory, and/or Databricks is preferred. Solid experience with BI and data visualization tools (e.g., Tableau, Power BI). Demonstrable experience managing projects, ideally involving both internal and external (vendor) teams. Exceptional communication and presentation skills, with a track record of effectively conveying complex insights to diverse audiences. Proven ability to document and formalize processes for wider market adoption. A strategic and adaptable mindset, able to thrive in a multicultural and fast‑paced regional environment. #J-18808-Ljbffr