We are seeking a highly motivated AI Researcher to join our core Data Science team. In this role, you will be at the forefront of tackling complex, high-impact business challenges by leveraging cutting-edge GenAI technologies, advanced AI research, and classical machine learning and statistical modeling.
You will not just be building models; you will be driving research from ideation to production. We are looking for a true self-learner, someone who thrives in an environment that demands both a strong sense of ownership over your deliverables and deep collaboration. You will work closely with fellow researchers, product managers, and software developers to translate abstract business problems into scalable data-driven solutions.
If you are passionate about staying ahead of the AI curve, building agentic workflows, and proactively driving your research initiatives forward within a collaborative team structure, this is the perfect role for you.
What You Will Do:
End-to-End Research & Ownership: Lead targeted research projects from initial hypothesis through to production-ready solutions. Take strong ownership of your work's performance and partner with engineering to ensure successful, scalable integration
Applied AI Research & Integration: Lead research into LLMs, agentic systems, and modern AI methods, then design and build the workflows that bring them into our ecosystem.
LLM Evaluation & Optimization: Contribute to and establish rigorous evaluation frameworks for LLMs to ensure accuracy, safety, and business alignment in practical applications.
Cross-Functional Collaboration: Act as a bridge between data, engineering, and product. Work with Developers to ensure seamless integration of ML features into the core product.
Continuous Innovation: Act as an internal advocate for emerging AI research and methodologies. Continuously read, experiment, and implement state-of-the-art techniques to advance our research agenda and accelerate research velocity.
Requirements: 3 to 5 years of proven industry experience working as an AI Researcher or Data Scientist in a fast-paced environment.
M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a closely related quantitative field.
Deep theoretical knowledge and hands-on experience with classical Machine Learning algorithms and advanced statistical modeling techniques.
Proven experience researching and building with advanced AI concepts, such as RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, autonomous AI systems, and rigorous LLM evaluation mechanisms.
Strong experience working with modern AI productivity and development tools (e.g., Claude Code, Cursor, GitHub Copilot, advanced prompting frameworks) to accelerate coding and research execution.
A demonstrated ability to teach yourself new concepts quickly. You proactively research, test, and propose state-of-the-art solutions rather than waiting for a rigid roadmap.
Excellent ability to communicate complex mathematical and technical concepts to non-technical stakeholders while matching the technical depth required to work seamlessly with Engineering.
Advantages:
While the core requirements above are essential, the following will make your application stand out:
Familiarity with or prior experience working in the Finance domain (e.g., risk modeling, algorithmic trading, fraud detection, financial time-series forecasting).
Knowledge and practical experience with causal inference techniques to measure true business impact beyond standard correlation.
Experience designing and training deep neural networks (e.g., PyTorch, TensorFlow) for complex unstructured data tasks.
This position is open to all candidates.