Data Scientist developing predictive models and automation workflows for the mortgage lifecycle. Collaborating with cross - functional teams to enhance operational efficiency and customer outcomes.
About the role
- Data Scientist designing and implementing analytical solutions using Python and AI technologies. Collaborating cross-functionally to deliver Generative AI solutions for business needs in a hybrid setup.
Responsibilities
- Design and develop data models and analytical solutions.
- Optimize data analysis processes and methodologies.
- Ensure data solutions meet business and technical requirements.
- Provide technical support for data science projects.
- Collaborate with stakeholders to address data science needs.
- Develop and maintain advanced Python-based applications in the Generative AI domain, ensuring high performance, reliability, and scalability.
- Implement and optimize Generative AI models, including GPT, LLAMA, Mistral, FLAN T5 and other cutting-edge AI technologies, to create innovative solutions and knowledge graph.
- Development of advanced RAG pipelines with proper embeddings, indexing, chunking, reranking, prompts and evaluation
- Collaborate with cross-functional teams to integrate AI functionalities into broader systems and applications.
- Utilize AWS/Azure/Databricks GPU machines to manage GPU memory effectively, maximizing performance and efficiency.
- Stay updated on the latest advancements in Generative AI, Python development practices, and cloud services to continually enhance our AI capabilities.
- Assist delivery leads in delivering Generative AI solutions to clients in a timely manner, ensuring client satisfaction and project success.
Requirements
- 4+ years of experience as a NLP and Python developer.
- Experience with Pandas, NumPy, Scikit, NLP a must have
- Key fundamentals in object-oriented design, data structures and systems.
- Ability to integrate multiple data sources into a single system.
- Familiarity with testing tools.
- Ability to collaborate on projects and work independently when required.
- Working knowledge of GitHub and Jira
- Ability to document requirements and specifications.
- Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
- 4+ years of experience in data science, building hands-on ML models.
- Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning
- Knowledge of advanced RAG pipelines with proper embeddings, indexing, chunking, reranking, prompts and evaluation
- Excellent programming skills in Python. Strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc
- SQL skills with SQL Server and Spark experience is preferred but not necessary.
- Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
- Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling.
- Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment
- Experience with cloud platforms such as Azure, AWS, Databricks is preferred.
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