Data Analyst

A profitable, well-established private AI technology company operating at the intersection of Sports Analytics, Machine Learning, and predictive modeling.

The company engineers sophisticated statistical algorithms and machine learning platforms designed to forecast sports outcomes, alongside real-time data platforms delivering live match intelligence to a paying international client base.

Operating with a tight-knit team of dozens of professionals, the organization combines financial stability and steady growth with deep analytical challenges in a fast-paced sports-tech ecosystem.

The company is located in the Sharon region and operates fully on-site from the offices.

Role Description-

• Serving as a Data Analyst within the core Research team, reporting directly to the Research Team Lead and taking end-to-end analytical ownership of high-volume sports data.
• Conducting in-depth statistical analysis on live and historical match data to identify predictive patterns, validate statistical hypotheses, and support machine learning models.
• Writing advanced, complex SQL queries, stored procedures, and data extraction workflows in Microsoft SQL Server to generate analytical datasets and business reports.
• Developing analytical scripts and data processing pipelines using Python (or R) to automate research processes and evaluate model accuracy.
• Collaborating cross-functionally with data scientists, researchers, product managers, and engineering squads to translate data findings into live platform features.
• Driving analytical projects independently from data extraction and cleansing to final statistical modeling and actionable insights.

Requirements-

• Proven hands-on industry experience as a Data Analyst (3–5 years) – Mandatory
• Advanced, expert-level proficiency in SQL and relational databases, specifically Microsoft SQL Server (complex queries, optimizations, data manipulation) – Mandatory
• Practical programming and data-scripting experience in Python or R for data manipulation and analysis – Mandatory
• Solid academic and practical foundation in Applied Statistics, Probability, and Statistical Modeling – Mandatory
• Genuine passion and deep familiarity with Sports (Soccer, Basketball, etc.) and sports analytics – Mandatory
• Proven ability to manage analytical projects independently End-to-End with high attention to detail – Mandatory
• Degree in Statistics, Mathematics, Computer Science, Industrial Engineering, Economics, or a related quantitative field – Significant Advantage