Data Analyst – Outsourcing / External Consultant

Who we are:

Atidot is a fast-growing InsurTech start-up building an innovative AI and Machine Learning platform aiming to revolutionize the life insurance industry. We empower insurers to become data-driven by producing actionable insights that inform decision-making and drive new business strategies at the corporate level.

As we continue to scale, we are looking for an experienced Data Analyst to work with us on an outsourcing / consulting basis, and support our R&D department. This is a unique opportunity for a highly capable, self-motivated professional to take ownership of data narratives and influence the core logic of our products while working in a flexible engagement model.

The role:

As an external Data Analyst, you will be responsible for modeling, analyzing, and reporting data across our platform. You will own analytical outputs and dashboards, extract KPIs, perform deep analyses, and contribute data-driven features to our machine learning models. You will work closely with internal teams, quickly understand business and client needs, and help deliver high-quality analytical outputs to our customers.

What you’ll do:

• Collaborate with the data team on building and implementing ML classification and regression models (e.g., customer churn, segmentation, recommender systems).
• Clean, transform, and ensure data quality throughout all stages of data acquisition and processing.
• Collect and analyze external data sources to support modeling and insights.
• Analyze large volumes of complex data involving multiple variables and business considerations.
• Translate data into clear business insights and articulate the story behind the numbers.
• Support and enhance reporting platforms and analytical dashboards.
  
  

• 2+ years of industry experience as Data Analyst in a DS team.
• Strong experience with code versioning platforms (e.g., Github).
• Excellent skills with the main Python data libraries: Pandas, Numpy, etc.
• Strong abilities in data extraction, exploration and analysis.
• Experience with feature engineering.
• Team player with good communication skills.
• Strong problem-solving and planning skills, with experience in breaking down large problems into smaller, manageable components.
• English fluency.
  
  

• Experience with advanced data visualization libraries, e.g., Seaborn, Plotly.
• Experience with statistical feature selection methods.
• Experience in Insurance or Fintech.
• Experience with Excel.