Data Scientist

Personetics is shaping the Cognitive Banking era, harnessing AI to help banks anticipate customer needs, provide actionable insights, and deliver intelligent financial guidance. Our platform continuously analyzes and leverages real-time transactional data, enabling banks to proactively support customers in managing their finances and reaching their goals. As industry leaders—yes, we really are leaders—we partner with the world’s top financial institutions, empowering over 150 million customers monthly across 35 global markets from offices in New York, London, Singapore, São Paulo, and Tel Aviv.

We are seeking an experienced Data Scientist to advance cutting-edge Machine Learning (ML) & Deep Learning (DL) research, champion Responsible AI best practices, and drive product innovation. This role offers the opportunity to develop and optimize ML models while also pioneering innovative AI applications under strict governance and ethical standards. You’ll work on both structured, production‑ready AI systems and experimental, next‑generation AI solutions, adapting based on business needs.

If you love rigorous ML development, creative AI prototyping, AND ensuring AI is built responsibly, this is the perfect role for you!

ML/DL Research & Applied Data Science

• Develop, optimize, and deploy ML/DL models aligned with business goals.
• Conduct data exploration, preprocessing, and model enhancement to improve performance.
• Implement robust model monitoring pipelines to ensure reliability and mitigate drift.
• Collaborate with engineering & product teams to integrate AI solutions into production systems.

New Product & Backlog Research

• Scout emerging technology trends and conduct market & internal backlog research to surface unmet customer needs.
• Evaluate and prioritize research findings, translating them into actionable, data‑driven proposals that influence the product roadmap.

• 6–10 years in Data Science, Machine Learning, or AI Research.
• Expert in Python ecosystem (PyTorch, TensorFlow/Keras, Hugging Face, Pandas, NumPy, Scikit-learn).
• Expertise in ML/DL modelling
• Strong analytical skills for structured & unstructured data and the ability to translate academic research into real‑world applications.
• Excellent communication & collaboration skills.
• Background in product-driven environments with rapid prototyping and iterative development.

• Generative AI Proficiency (e.g. LLMs, RAG, etc.).
• Experience with cloud platforms (AWS, Azure, GCP).
• Experience with multimodal AI solutions (text, image, audio).
• Background in FinTech, Banking.