Data Analyst

An established technology startup that develops an advanced AI-driven research assistant tailored for the clinical, medical, and pharmaceutical sectors.

The platform utilizes sophisticated natural language processing and generative AI to map complex healthcare data, synthesize biomedical datasets, and accelerate scientific discovery.

Having secured a substantial Series A funding round from prominent investors, the company

operates with a growing team of dozens of professionals, supporting an active portfolio of global enterprise clients including leading pharmaceutical corporations, research hospitals, and biotech ventures.

The company is located in Tel Aviv (train-accessible) and operates on a hybrid model with flexibility for one day of remote work.

Key Responsibilities-

• Designing and executing advanced database queries over high-scale clinical and pharmaceutical data stores.
• Writing performance-tuned, scalable data processing scripts and statistical models using Python.
• Performing deep data exploration, cleaning, and structural mapping utilizing data manipulation frameworks like Pandas.
• Building automated analytical pipelines to track data trends, evaluate information consistency, and streamline incoming client data ingestion.
• Translating intricate healthcare data architectures into structural insights that directly drive the training and calibration of the AI research model.

Requirements-

• 3 years of professional experience operating as a Data Analyst, Data Specialist, or Business Intelligence Engineer (Mandatory).
• Strong, hands-on programming and scripting proficiency utilizing Python, with a deep focus on data science ecosystems and libraries like Pandas (Mandatory).
• Advanced expertise writing complex, performance-optimized queries in SQL to extract data from structured and unstructured repositories (Mandatory).
• Proven professional experience working within a healthcare, medical device, biotech, digital health, or pharmaceutical organization (Mandatory).
• Exceptional analytical capability, with a strong background in manipulating multi-source datasets, resolving data anomalies, and understanding clinical domains.