Data Scientist

Skillset required for Python AI/GenAI Developer:

A solid foundation in Python programming is essential, along with familiarity with popular AI libraries/frameworks such as Langchain, TensorFlow, PyTorch, scikit-learn, and spaCy.

Demonstrated proficiency in developing AI solutions using Azure services, including Azure AI Search, Azure OpenAI APIs, and Azure SQL Database.

In-depth knowledge of search algorithms, indexing techniques, and retrieval models for effective information retrieval tasks. Familiarity with search platforms like Elasticsearch or Azure AI Search is highly advantageous.

Hands-on experience with RAG architecture and its application in natural language processing tasks is a must.

Ability to proficiently manipulate data, perform complex queries, and conduct data transformations using SQL Server.

A solid understanding of machine learning and deep learning techniques, particularly those relevant to natural language processing tasks such as text extraction, text classification, sentiment analysis, named entity recognition, and summarization.

Ability to preprocess and clean large datasets efficiently using SQL/Python and other data manipulation tools. Experience with techniques such as data normalization, feature engineering, and data augmentation is preferred.

Expertise in working with healthcare data standards (ex. HIPAA and FHIR), sensitive data and data masking techniques to mask personally identifiable information (PII) and protected health information (PHI) is essential.

Knowledge of cloud computing principles and experience in deploying, scaling, and monitoring AI solutions on cloud platforms like Azure.

Ability to communicate complex technical concepts effectively to technical and non-technical stakeholders and collaborate with cross-functional teams.

Analytical mindset with a keen attention to detail, coupled with the ability to solve complex problems efficiently.

Knowledge of cloud cost management principles and best practices to optimize cloud resource usage and minimize costs.

Must Have:

Minimum of 10 years’ experience as a data scientist.

Deep hands-on experience using Python.

Hands-on experience scaling POC to production

Hands-on experience with Azure Cloud eco-system

Hands-on experience using tools such as Document Intelligence (formerly Azure Form Recognizer), Snowflake, Azure AI Search, Azure OpenAI

Experience working with PII/PHI

Hands-on experience working with unstructured data.

Must have implemented a use case using RAG architecture.