TeqAtlas

Role overview

We are looking for a Data Analyst who will contribute to building the analytical logic of the product and work with large-scale, socially structured datasets.

This role goes beyond traditional reporting analytics. The focus is on exploratory analysis, structuring complex data, identifying meaningful signals, and contributing to the logic behind search and matching mechanisms.

Key responsibilities

• Perform exploratory analysis of large datasets to identify patterns and signals affecting result quality and relevance.
• Design and maintain controlled vocabularies (skills, titles, industries, locations, etc.).
• Normalize and structure unorganized and semi-structured data.
• Build and maintain hierarchies, classifications, and logical relationships between entities.
• Contribute to the analytical logic behind search and matching mechanisms.
• Formulate and validate hypotheses using data-driven approaches.
• Evaluate the impact of different data signals on outcomes.
• Visualize and communicate analytical findings to support product decisions.
• Work closely with founders and the product team.

Required technical skills

• 3+ years of experience as a Data Analyst or in a similar analytical role.
• Advanced SQL proficiency: complex joins, aggregations, query optimization.
• Experience with BI tools: Tableau (preferred) or Power BI 
  BI tools are used for research and analytical exploration rather than routine dashboarding.

• Strong data visualization skills.

   

Required analytical & cognitive skills

• Strong critical thinking and hypothesis-driven approach.
• Ability to work with ambiguous problems without predefined solutions.
• Experience working with unstructured or semi-structured data.
• Ability to design hierarchies, classifications, and entity relationships.
• Ability to translate business questions into analytical models.
• High attention to detail and data quality.

• Research-oriented mindset and proactive problem-solving approach.

   

Nice to have

• Experience with Python /R for data analysis: pandas, NumPy, etc.
• Experience with ETL processes and data pipelines.
• Experience or familiarity with graph databases (e.g., Neo4j).
• Experience working with social, network-based, or relationship-driven datasets.