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Salary
≈ $60k – $165k per year (Estimated)
Location
Hybrid (Givatayim, Israel)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 13, 2026.

Overview
Company
Impact
Profile match
Personetics is an Israeli company that adds data driven personalisation and financial guidance to banking applications. Its engine analyses transaction data to surface insights, savings suggestions and proactive alerts to customers. The platform is used by many of the largest retail banks in North America and Europe.

Description

Join Personetics as an Intermediate Applied Data Scientist, where you'll work with a dynamic team to analyze complex data and deliver innovative solutions for our clients. Utilize your expertise to drive data-driven decision-making and support the development of cutting-edge financial technology.

About the position

We are hiring an Applied Data Scientist to build the models that turn raw transaction data into the insights our banks’ customers see every day.

The stack is deliberately wide: classical ML on tabular data, deep learning, LLM-based systems, and agentic flows. We choose the right approach for each problem, balancing analytical quality, production readiness, and time to market. You drive the analytical work, working closely with Product and Engineering to take ideas from evidence through production.

Responsibilities

  • Analyze and interpret complex datasets to identify trends and patterns.
  • Collaborate with cross-functional teams to develop data-driven solutions.
  • Build and maintain predictive models to enhance business decisions.
  • Communicate findings and insights effectively to stakeholders.
  • Stay updated with the latest data science technologies and methodologies.
  • Contribute to the continuous improvement of data processes and systems.

Requirements

  • Bachelor's degree in Data Science, Computer Science, or related field.
  • 3+ years of experience in applied data science or a similar role.
  • Proven experience with machine learning algorithms and statistical modeling.
  • Proficiency in programming languages such as Python or R.
  • Strong analytical skills and ability to work with large datasets.
  • Excellent communication and teamwork skills.
  • Experience with data visualization tools like Tableau or Power BI.

Nice to have

  • FinTech or banking experience.
  • Transformer models - fine-tuning and production inference.
  • Experience taking a model into production, including monitoring and post-launch iteration.
  • Cloud platforms (AWS, Azure).
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