Data Scientist

An early-stage, fast-growing FinTech AI startup developing an advanced Data Analytics and Machine Learning platform for corporate evaluation, quantitative financial modeling, and data-driven decision-making.

Backed by substantial early-stage funding and generating revenue from day one, the company operates with a lean, elite core team.

They offer a true, dynamic startup environment free of corporate bureaucracy where engineers have direct ownership and the unique opportunity to build core products from the ground up.

Located in a central high-tech hub in the Tel Aviv area with excellent public transit access, operating on a hybrid work model (1 WFH day per week).

Position Overview

• Hands-On Data Scientist joining a founding engineering squad to build predictive frameworks, tabular/financial data pipelines, and quantitative decision systems.

• Developing end-to-end Machine Learning models tailored to complex business scenarios, translating raw telemetry and behavioral metrics into actionable predictive power.

• Designing features, analyzing multi-source datasets, and working extensively with time-series forecasting, statistical modeling, and risk evaluation.

• Partnering directly with domain experts and product leadership to continuously iterate on model architectures per business use-case.

• Core Domain & Ecosystem- Data Science, Classical Machine Learning, Predictive Modeling, Time-Series Forecasting, Statistical Analysis (Regression, Survival Analysis, Bayesian Methods), Python, Feature Engineering, Financial Analytics / Quantitative Data.

Requirements-

• 4+ years of professional experience as a Data Scientist within an established, hands-on Data Science group – Mandatory

• Proven, hands-on track record building, tuning, and deploying Predictive Models into production environments – Mandatory

• Deep expertise in Classical Machine Learning techniques and advanced statistical modeling (e.g., Regression, Time Series, Survival Analysis, Bayesian Methods) – Mandatory

• Advanced programming and modeling mastery in Python – Mandatory

• Strong quantitative academic background or solid foundation in Mathematics, Statistics, Computer Science, or a related quantitative field – Mandatory

• Hands-on experience working with complex, messy real-world datasets and translating algorithmic outputs into tangible business impact – Mandatory

• Prior background in elite technological military units or high-caliber R&D environments – Strong Advantage

• Self-driven problem solver with a strong ownership mindset and a passion for early-stage engineering challenges – Mandatory

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