Data Analyst

This is us: 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, producing actionable insights that inform decision-making and drive new business strategies at the corporate level. We are scaling up and looking for a Data Analyst to join our R&D department. This is a unique opportunity for an experienced, self-motivated individual to take ownership of our data narratives and influence the core logic of our products.

As a Data Analyst you will be responsible for modeling and reporting all things data. You’ll own our reporting platform and analytic dashboards, extract KPIs, perform deep analysis on our data, create data-driven features for our models, and manipulate our algorithmic systems to deliver the best outputs to our clients. Prioritising tasks and quickly understanding client needs will prove a crucial aspect. Love for data is also necessary, along with a keen sense of curiosity and eagerness to learn new things on a daily basis.

What you'll do:

• Being part of the data team, assist in building and implementing ML classification and regression models for customer churn and segmentation, and recommender systems.
• Clean, transform and ensure data quality throughout all stages of acquisition and processing.
• Collect and analyze external data for our models.
• Analyze large volumes of complex data that requires consideration of multiple factors to interpret the information.
• Understand and explain the business process and the story behind the data.
  
  

• 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.