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Über
Cyndx is an Artificial Intelligence and Natural Language Processing (NLP) platform that offers'search and discovery' solutions for entrepreneurs, start-ups, investors, and acquirers. Our subscription-based solution helps enhance capital raising, acquisitions, and other business opportunities. Our platform hosts data on over 30 million companies world-wide and is used by some of the largest financial institutions in the world. We are looking for a Lead Data Scientist to work on leveraging text and financial data to build machine learning models that encapsulate the ecosystem of a banker's lifecycle. We are looking for individuals who thrive in fast-paced environments, are creative problem solvers and get their kicks from implementing solutions for non-trivial machine learning problems designed for the financial world and working with a team who raises the bar. In this role, you will be working with a team of AI engineers and data scientists and are responsible for the design and development of proprietary AI algorithms, including but not limited to fine-tuning large language models for semantic search engines, financial data point estimations, recommendations, and trend predictions, that would make Cyndx unique in the Fintech market space. This role will be located in our West Palm Beach office. Please note that we are currently working on a hybrid model and are in the office for four days and remote for one day each week. Remote work is not a possibility in this role. Salary Range: $140,000 - $180,000 Responsibilities
Design and develop data engineering pipelines to ingest, transform, and integrate new financial data sources Maintain and enhance our models using time series analysis, machine learning, and deep learning techniques (e.g. 'Projected To Raise') Implement and fine-tune open-source LLMs for specialized financial text generation, summarization, and classification tasks Create and maintain features in our FastAPI middleware service, including developing new endpoints and optimizing existing ones Participate in code reviews, testing, and deployment processes using modern CI/CD practices Develop and suggest solutions and strategies to business challenges Work together with engineering and product development teams Requirements
4-8 years' experience of working as Data Scientist with significant experience with Gen AI, vector databases and traditional machine learning Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or related STEM field Strong foundation in statistics, probability, calculus, and linear algebra, particularly as applied to time-dependent data Experience with Python programming and data science libraries (NumPy, Pandas, scikit-learn, PyTorch or TensorFlow) Knowledge of NLP concepts and techniques, including word embeddings, transformer architectures, and large language models Experience working in productionizing code and deploying models to cloud environments, preferably GCP (BigQuery, Cloud Run, GCS) or similar platforms Proficiency in SQL and experience working with relational databases Strong research mind to be able to read and understand the latest research in AI and NLP Preferred Qualifications (Nice to Have)
Experience with financial data, financial modeling, or quantitative analysis Familiarity with time series forecasting techniques Experience with infrastructure-as-code tools like Terraform Knowledge of Docker containerization and Kubernetes orchestration Prior work with agentic AI systems or RAG (Retrieval-Augmented Generation) architectures Understanding of MLOps practices and tools Experience contributing to open-source projects or building reusable software components
Sprachkenntnisse
- English
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