Senior Data Scientist

Our client is an international investment firm that supports the most ambitious and talented entrepreneurs and high growth companies to achieve their goals. They invest in high growth, dynamic situation buyouts and growth capital investments. They are back exceptional entrepreneurs and management teams in companies creating sustainable high growth and strategic value.

You will be responsible for working on the client’s internal platform, which is used for analyzing companies for potential future investments.

• Programming Languages: Python to advanced level, covering EDA, model training/testing, hyperparameter tuning etc.
• Frameworks: Must have expertise with standard frameworks/libraries such as scikit-learn and pandas. Proficiency with NLP libraries like NLTK, SpaCy, and scikit-learn.
• Databases: SQL expertise, and familiarity with MySQL, MongoDB, etc.
• NLP: Knowledge of NLP foundations, including vectorization methods. Application of pre-trained models such as BERT, and fine-tuning of such models.
• Machine learning foundations: Standard techniques in supervised learning, including ensemble methods for classification and regression.
• Communication: Clear and precise verbal and written communication.
• Autonomy: Completion of research projects with an NLP focus, requiring only periodic supervision. Self-directed solutions to tactical/intermediate problems.

• Infrastructure: Experience with at least one major cloud platform, ideally GCP. Familiarity with cloud services such as BigQuery is preferred.
• Front-end: Experience of visualization using interactive dashboards such as Streamlit or Dash. Basic understanding of front-end technologies (HTML, CSS, JavaScript) is a plus.
• Frontier NLP: Application of recent LLMs, including fine-tuning.
• Statistics: Expertise in classical statistical techniques, including significance testing.
• Domain-specific: Completion of finance-related projects using unstructured data, including topic classification.