Data Scientist

Description

Nayax is a global fintech company (NASDAQ; TASE: NYAX) and a leading provider of cashless payment, consumer engagement, and business management solutions for the unattended retail sectors.

We are currently seeking a hands-on Data Scientist to Nayax Capital - Nayax Capital is the embedded financing engine within Nayax LTD , it delivers fast, predictable B2B financial tools and instruments that helps operators grow without friction while turning transactions and telemetry into flexible B2B capital that is built right into the platform Nayax customers already use

The Data Scientist needs to research and analyze multiple financial datasets (payments, loans/credit, and adjacent instruments) and turn findings into revenue-generating insights. You’ll have wide autonomy to explore data yet stay tightly aligned to business outcomes helping us shape pricing, new products, underwriting/credit strategies, and operational efficiency.

Beyond analysis, you’ll lay the foundation for our data practice: lightweight processes, governance, and working methods that scale globally across the USA, EMEA and APAC. The ideal candidate brings a startup mentality, is fluent in fintech models (neobanks, cloud-native stacks, digital banking), and is comfortable coding, querying across heterogeneous databases (including federation), and leveraging modern AI tooling, preferably on AWS.

The Data Scientist will report directly to the CEO.

Key Responsibilities

• Own the research agenda across internal and external financial databases; discover signals that drive new revenue and margin expansion.
• Translate ambiguous business questions into crisp analytical plans, metrics, and experiments.
• Query and join data across multiple systems (SQL/NoSQL, data warehouses, APIs); use federated query engines (e.g., Athena/Presto/Trino) where appropriate.
• Build repeatable analysis assets (SQL models, notebooks, lightweight pipelines) and executive-ready artifacts (dashboards, briefs).
• Partner with Product, Finance, Risk/Credit, Operations and Sales to, set success metrics, and track impact.
• Prototype and apply AI/ML where it matters (e.g., segmentation, propensity, anomaly/fraud signals, pricing experiments) using AWS services (e.g., SageMaker/Bedrock) or equivalent.
• Establish pragmatic data governance: source cataloging, documentation, versioning, code review standards, and data quality checks.
• Champion best practices in privacy/security and compliance in a payments/credit context.
  
  

Requirements

• Bachelor’s degree in Mathematics/ Engineering/ Computer Science/ Data Science or a related technical field - Must
• 4+ years in Analytics/ Data Science/ Data Engineering or quant research roles - Must
• Experince wirh fileds of fintech/ payments credit exposure - Advantage (how payment flows, chargebacks, interchange, and basic credit/underwriting work) Preferably in a fintech company or other startup organization focused on B2B financial solutions.
• Strong SQL experince - Must (window functions, performance tuning)
• Experince with Python for analysis/ETL - Must (NumPy, pandas/pyarrow; basic PySpark a plus).
• Comfort with AWS data stack - Advantage (S3, Glue/Athena, Redshift or Snowflake-on-AWS; SageMaker/Bedrock familiarity preferred).
• Experience querying across heterogeneous databases and/or federated queries; able to design sane data models and joins across messy sources.
• Proven track record turning analysis into business outcomes (pricing, product, revenue ops, credit/risk insights).
• Data visualization competency (qliksense, Power BI) and clear writing/presentation for executives.
• Startup mindset: self-directed, bias to action, comfortable with ambiguity; willing to build processes while shipping work.
• Solid engineering hygiene: Git, reproducible notebooks/pipelines, documentation, and basic testing.
• Working knowledge of data governance, privacy, and controls expected in financial services.
  
  

What Makes This Role Exciting

• Enjoy autonomy and a startup-like environment, where your creativity, initiative, and solutions have a visible impact.
• Work with diverse financial datasets and uncover insights that directly impact revenue, pricing, and credit strategies.
• Shape the company’s global data culture, governance, and best practices across USA, EMEA, and APAC.
• Leverage cutting-edge cloud-native architectures, AI/ML tools, and federated data systems to solve real-world fintech problems.
• Collaborate closely with Product, Risk, Sales, and Finance teams, ensuring your analyses drive tangible business outcomes.
• Build foundational processes, pipelines, and analytical assets that scale across the organization and set new standards.
  
  

Learn More About Nayax

Nayax is a global fintech company (NASDAQ; TASE: NYAX) providing an end-to-end platform for payments, consumer engagement, and business operations.

Founded in 2005, Nayax empowers businesses to grow revenue, reduce operational costs, and deliver seamless commerce experiences. Our customer-first mindset and commitment to in-house innovation have positioned us at the forefront of the cashless payment revolution, serving the unattended and retail sectors around the world.

We support over 80 payment methods in 50+ currencies, hold a European payment institution license, and have formed strategic partnerships with global financial institutions to deliver powerful, scalable solutions.

With more than 1,100 employees across 11 global offices, Nayax operates in 62+ countries. Our global headquarters in Herzliya Hills, Israel, is our largest site, housing over 600 employees across 20+ departments — just a short walk from the train station and designed for collaboration and growth.

At Nayax, we believe in creating long-term impact through loyalty tools, omnichannel solutions, and an agile ecosystem of value-added services. We're proud to support businesses in reaching new heights and we're always looking for innovative, passionate individuals to join us.