Senior Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with a contract length of "unknown," offering a pay rate of "unknown." Key skills include machine learning, NLP, and experience with PyTorch and TensorFlow. Strong Python background and cloud platform knowledge are required.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 10, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Unknown
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Raleigh, NC
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🧠 - Skills detailed
#OpenSearch #Clustering #BERT #Langchain #NLP (Natural Language Processing) #AWS (Amazon Web Services) #ML Ops (Machine Learning Operations) #API (Application Programming Interface) #Python #Data Science #Elasticsearch #TensorFlow #Datasets #"ETL (Extract #Transform #Load)" #Hugging Face #Data Modeling #Classification #Cloud #Code Reviews #Azure #ML (Machine Learning) #Keras #Deep Learning #Libraries #Databases #NoSQL #PyTorch #Distributed Computing #SpaCy #GCP (Google Cloud Platform) #Transformers #AI (Artificial Intelligence) #Jupyter #Scala #Spark (Apache Spark) #Data Engineering #Deployment
Role description
As a Senior Data Scientist , you will play a crucial role in engineering modern businesses to improve everyday life. You will be instrumental in driving new product development within a collaborative team environment, writing production code in both run-time and build-time environments. Your role will involve proposing and building data-driven solutions to address high-value customer problems. You will work with large-scale natural language datasets, including matter and contract repositories, invoice/legal spend data, and work management. Your contributions will be pivotal in prototyping new ideas and collaborating with other data scientists, product designers, data engineers, front-end developers, and expert legal data annotators. You will experience the dynamic culture of a start-up while leveraging the extensive resources of an established company. An ideal candidate will possess a strong passion for advancing beyond Jupyter Notebooks and consistently delivering production-ready code each sprint.. RESPONSIBILITIES β€’ Develop and implement LLM-based applications tailored for in-house legal needs, ensuring they align with Cognizant's commitment to excellence and innovation β€’ Evaluate and maintain our data assets and training/evaluation datasets, ensuring they meet the highest standards of integrity and quality. β€’ Design and build pipelines for preprocessing, annotating, and managing legal document datasets, fostering a customer-centric mindset. β€’ Collaborate with legal experts to understand requirements and ensure models meet domain-specific needs, working as one team. β€’ Conduct experiments and evaluate model performance to drive continuous improvements, raising the bar in all deliverables. β€’ Evaluate AI/ML and GenAI outcomes, both human and automated, to ensure accuracy, reliability, and alignment with business objectives. β€’ Interface with other technical personnel or team members to finalize requirements, demonstrating ownership of outcomes. β€’ Work closely with other development team members to understand complex product requirements and translate them into software designs, ensuring ethical choices in all actions. β€’ Successfully implement development processes, coding best practices, and code reviews for production environments, embodying Cognizant's values in every task. REQUIREMENTS β€’ Strong hands-on experience and foundations in machine learning, including dimensionality reduction, clustering, embeddings, and sequence classification algorithms. β€’ Experience with deep learning frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers. β€’ Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, TensorFlow, Keras, PyTorch, Flair, BERT. β€’ Practical experience with large language models, prompt engineering, fine-tuning, and benchmarking using frameworks such as LangChain and LlamaIndex. β€’ Strong Python background. β€’ Knowledge of AWS, GCP, Azure, or other cloud platforms. β€’ Understanding of data modeling principles and complex data models. β€’ Proficiency with relational and NoSQL databases as well as vector stores (e.g., Postgres, Elasticsearch/OpenSearch, ChromaDB). β€’ Knowledge of Scala, Spark, Ray, or other distributed computing systems is highly preferred. β€’ Knowledge of API development, containerization, and machine learning deployment is highly preferred. β€’ Experience with ML Ops/AI Ops is highly preferred.