Data Analyst

Sedric is an emerging leader in the field of AI-based compliance risk management for B2C fintechs. Backed by top-tier VCs, the company has an R&D center in Tel Aviv, a global customer base, and sales operations in the US, Europe, and Australia.

Sedric’s SaaS platform seamlessly analyzes customer interactions, integrating them across multiple channels (video, voice & chat) to prevent, detect and intelligently mitigate compliance and reputation violations.

We are looking for a team player to join our growing data team. The right candidate has great analytical skills, can tell a story through data, has a fine eye for detail, and is a problem-solving fan.

You will ensure that our data and insights are actionable to drive decisions across the business and communicate data-driven insights and recommendations to key stakeholders at all levels.


Responsibilities:

  • Managing master data, including creation, updates, and deletion.
  • Managing users and user roles.
  • Provide quality assurance of imported data, working with quality assurance analysts if necessary.
  • Commissioning and decommissioning of data sets.
  • Helping develop reports and analysis.
  • Managing and designing the reporting environment, including data sources, security, and metadata.
  • Supporting the data warehouse in identifying and revising reporting requirements.
  • Supporting initiatives for data integrity and normalization.
  • Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
  • Generating reports from single or multiple systems.
  • Troubleshooting the reporting database environment and reports.
  • Evaluating changes and updates to source production systems.

Requirements:


  • Bachelor’s degree in computer science.
  • 2+ years experience as a data analyst or similar position
  • Ability to work with stakeholders to assess potential risks.
  • Ability to analyze existing tools and databases and provide software solution recommendations.
  • Ability to translate business requirements into non-technical, lay terms.
  • High-level experience in methodologies and processes for managing large-scale databases.
  • Demonstrated experience in handling large data sets and relational databases.
  • High-level written and verbal communication skills.

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