Senior Data Scientist

About the job

We are looking for an experienced senior data scientist to join the data science team. You’ll have the opportunity to make a significant impact by creating products that beat the investment market.

Responsibilities

• Machine Learning: design, research, analyze, develop, and implement predictive models to address complex business problems.
• Data Science Group focal point for aspects of classical ML algorithms, LLM implementation and statistics
• Software Engineering: design, develop, test and implement data pipelines infrastructure, work closely with group members and peers
• Collaboration: Work closely with cross-functional teams including Back End engineering, Data Engineering, Investment portfolio managers, Devops, and Front End teams to deliver ML to production.
• Stay updated with the latest research and advancements in MLOps, time-series prediction and Gen-AI.

Requirements

• B.Sc in Machine Learning, Computer Science, Software Engineering, Statistics or related field
• 5+ years of startup experience as a Data Scientist – handson research, data analysis, implementation of predictive models and research management
• Experience with Machine Learning for time-series prediction and tabular data: Proven track record in productization of ML models
• Proficiency in Python, SQL and Vibe coding: Strong coding skills with a focus on writing efficient and scalable ML code
• Production Experience: Demonstrated ability to deploy ML models in production, ensuring reliability, scalability, and real-time processing
• Communication: Create clear, concise, and actionable reports to communicate insights to stakeholders.
• Initiator and Promoter: Self-starter who actively proposes new ideas and promotes innovative solutions
• Learner: Passion for continuous learning, staying updated on the latest SW and ML trends, tools, and research
• Flexible Mindset: Adaptability in approaching problems and adjusting models or strategies as needed

Preferred qualifications

• Master's or Ph.D. Degree in a quantitative field.
• Experience fine-tuning and deploying large language models using frameworks such as Hugging Face Transformers, vLLM, or SageMaker.
• Technologies: AWS, Airflow, Docker, Kubernetes, MLFlow