Data Scientist

Metro Global Solution Center (MGSC) is internal solution partner for METRO, a €31.6 Billion international wholesaler with operations in more than 30 countries. The store network comprises a total of 623 stores in 21 countries, of which 522 offer out-of-store delivery (OOS), and 94 dedicated depots. In 12 countries, METRO runs only the delivery business by its delivery companies (Food Service Distribution, FSD).

HoReCa and Traders are core customer groups of METRO. The HoReCa section includes hotels, restaurants, catering companies as well as bars, cafés and canteen operators. The Traders section includes small grocery stores and kiosks. The majority of all customer groups are small and medium-sized enterprises as well as sole traders. METRO helps them manage their business challenges more effectively.

MGSC, location wise is present in Pune (India), Düsseldorf (Germany) and Szczecin (Poland). We provide HR, Finance, IT & Business operations support to 31 countries, speak 24+ languages and process over 18,000 transactions a day. We are setting tomorrow's standards for customer focus, digital solutions, and sustainable business models. For over 10 years, we have been providing services and solutions from our two locations in Pune and Szczecin. This has allowed us to gain extensive experience in how we can best serve our internal customers with high quality and passion. We believe that we can add value, drive efficiency, and satisfy our customers.

Website:

Company Size:

Headquarters: Pune, Maharashtra, India

Type: Privately Held

Inception: 2011

Job Description

Your Responsibilities:

• Building and maintaining dashboards tailored to the target audience to track key KPIs and in-depth reports;

• Re-engineering the KPI logic to reflect the relevant data to be considered and to observe the cascading of the KPI tree;

• Digging into data to uncover new use cases and identify potential areas for improvement;

• Identifying and assisting with resolving data quality issues for accurate tracking and reporting;

• Collaborating closely with product teams and stakeholders to enable data-driven processes;

• Developing new KPIs as needed;

• Storytelling based on various data sets builds up narratives and graphic visualizations meant to communicate data driven insights and to influence data driven decision making;

• Promoting and educating product teams and (potential) stakeholders about data usage.

• Oversee the entire data science project lifecycle, from project scoping and planning to successful execution and delivery. You will manage resources effectively, prioritize tasks, and ensure projects are completed on time and within budget.

• Contribute your in-depth knowledge of data science methodologies, algorithms, and tools. You will guide your team in the development and implementation of advanced analytics solutions that address complex business challenges.

Qualifications

• Proven ability to work collaboratively across cross-functional teams within large organizations, fostering alignment and driving impactful outcomes.

• Strong analytical and conceptual thinking skills, with a keen ability to translate complex data into actionable insights.

• Demonstrated experience in data visualization using platforms such as Looker Studio (preferred), MicroStrategy, Tableau, or other BI tools, tailored to diverse audiences.

• Solid understanding of Google Cloud Platform (GCP) analytical technologies, including BigQuery ML, IAM, and Vertex AI for scalable machine learning workflows and model deployment.

• Skilled in evaluating data coverage, quality, drift, bias, leakage risk, and schema health, with the ability to quantify issues using metrics such as missingness, uniqueness, and outlier detection.

• Advanced expertise in data science and machine learning, including classification, regression, clustering, and optimization techniques. Additional knowledge in causal inference, data engineering best practices, and data visualization.

• Proficient in SQL (BigQuery) and Python, with hands-on experience using libraries such as scikit-learn, TensorFlow, PyTorch, and Polars.

• Experience leveraging Vertex AI for end-to-end ML lifecycle management, including training, tuning, deployment, and monitoring of models in production.

• Self-aware, positive, and deeply committed to customer-centric solutions and continuous improvement.

• Excellent fluency in English, both written and verbal, enabling effective communication across global teams.