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Data Scientist:

Our direct client, a fast-growing fintech firm, is seeking a Data Scientist.  The AI/ML team is developing cutting edge solutions to establish a unique competitive edge for the company. The Data Scientist role will play a key role in developing AI models and engineering firm’s core machine learning and AI products. This individual will be working in a collaborative team environment across machine learning, product management, data engineering, and software engineering teams. The ideal candidate will be passionate about leveraging machine learning techniques to drive innovation and have a strong background in researching and developing AI models.

This position is based in New York City, 4 days per week onsite is expected the base salary is in the $140-160K range, DOE, plus bonus and stock options.

Responsibilities

• Build and integrate AI/ML/DS tools and workflows to address business needs and increase business efficiency. 
• Support the design, development, training, and deployment of AI/ML models and engineering solutions to solve business problems through a full development and production cycle in the FinTech domain. 
• Build and leverage new and existing tools for Large Language Model (LLM), Natural Language Processing (NLP), Optical Character Recognition (OCR), and intelligent document processing tasks. 
• Evaluate and compare the performance of different AI/ML algorithms and models. 
• Contribute to the improvement of Machine Learning Operations (MLOps) pipelines and procedures to ensure efficiency, scalability, and maintainability. 
• Ensure the reliability, robustness, and scalability of machine learning models in production environments. 
• Collaborate with cross-functional teams, including machine learning engineers, product managers and full stack engineers, to deliver scalable machine learning solutions. 

Qualifications

• 4+ years of experience as a hands-on data scientist or AI/ML engineer in AI/ML/DS fields 
• Advanced degree in a relevant field such as AI, ML, Data Science, mathematics, or computer science. 
• Experience building ML and AI models and systems in a production environment in at least Generative AI/LLM or NLP applications 
• Experience working with LLM, such as GPT-4, Llama 3, Mistral, and other commercial or open-source models in a production environment 
• Knowledge of NLP techniques, including text data preprocessing (tokenization, stemming, and text normalization, etc.) and information extraction (summarization, and question answering, etc.) 
• Proficiency in programming languages in Python, and libraries/frameworks like TensorFlow, PyTorch, spaCy and scikit-learn, etc 
• Strong knowledge of machine learning algorithms and statistical techniques, their limitations, and implementation challenges 
• Experience with cloud platforms and distributed computing environments, such as AWS, Google Cloud, or Azure 
• Direct contributions to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results 
• Strong problem-solving skills and able to work independently and collaboratively in a fast-paced, agile environment 
• Strong communication skills and able to effectively articulate technical concepts to both technical and non-technical audiences 
• Experience with data visualization tools and techniques to effectively communicate and present findings 
• Publication record as a lead author or essential contributor at top venues such as CHI, NeurIPS, UIST, ICML, ICLR, ACL, EMNLP, CVPR, AAAI, and/or ICAPS 
• Portfolio of personal projects on Github, BitBucket, Google Colab, Kaggle, etc. 
• Understanding of regulatory and compliance requirements in the financial industry and their implications for machine learning applications 
• Experience with software development best practices, including source control (Git), CI/CD pipelines, testing, and documentation 
• Familiar with database integration principles and practices, including SQL and NoSQL databases and data warehouse solutions, such as Snowflake 
• Experience with data transformation tools, such as dbt, and orchestration tools such as Airflow 

Job ID: 5412