Principal Data Scientist

WWhat will you be responsible for? 

• Performs advanced statistical analyses to identify patterns and trends and opportunity assessments to assist in delivering optimal healthcare management and decision making. 

• Designs data visualizations and determines the best way to present data in a clear understandable format using reports, drilldowns, tables, gauges, graphs, charts, and other intuitive graphical add-ons. 
• Experience working with Gen-AI, expertise in fine-tuning transformer-based models / LLMs- GPT, Llama, PaLM, BERT and RAG models. 
• Fine-tuning of Large Language Models (GPT/ PaLM/ Llama) to meet specific business requirements. 
• Develop and implement machine learning models using a variety of techniques (supervised and unsupervised learning models including NLP, Deep learning Models, and Predictive Analytics) 
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes. 
• Manage and optimize processes for data intake, validation, mining, and engineering as well as modelling, visualization, and communication deliverables. 
• Prepares and delivers results to leadership with analytic insights, interpretations, and recommendations. 
• Understanding data storage and data sharing methods. 
• Understanding healthcare business operations. 
• Strong proficiency in: Python, PySpark, SQL, R & have experience in machine learning libraries & frameworks such as TensorFlow, PyTorch, or Keras. 
• Deep expertise in traditional as well as modern statistical & ML techniques like regression, support vector machines, Regularization, Boosting, Random Forests & other ensemble methods. 
• Proficiency in developing NLP models using: Nltk, spacy, Genism , Word 2 Vec , Seq 2 seq , transformers , BERT etc. 
• Prior hands-on experience in analysing large and complex data sets, data reliability analysis, quality controls and data processing, with focus on model validation practices.  

Who are we looking for? 

• 12 yrs. of professional work experience preferable in management consulting or high growth start-ups preferably in healthcare and 8-12+ years of experience in a data analytical role. 
• Bachelor's degree in mathematics, statistics, healthcare administration, or related field. 
• Master's degree advantageous. 
• 5+ years of experience in Python, SQL, R, SAS 
• Designing, developing, and implementing AI/ generative AI models & algorithms to solve complex problems and drive innovation across organization. 
• Lead all stages of AI/ML solutions implementation: Gathering business requirements & understanding, data requirements for the solution build, any constraints (data /business), data exploration/solution design, machine learning models development, active collaboration with model risk team to ensure high quality model deployment & minimize enterprise risk. 
• Lead the implementation of AI solutions to deliver business impact with focus on value, success criteria alignment, scalability, and operationalization. 
• Collaborating with cross-functional teams to define project requirements and objectives, ensuring alignment with overall business goals for integration, sign-off and deploying machine learning models into production. 
• Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders. 
• Engage team members, project managers & business stakeholders in the analysis and interpretation of experimentation results & ensuring feedback is incorporated as appropriate into models. 
• Drive best practices throughout development process and publish learnings/feedback for continuous learning. 
• Lead/drive and accelerate innovations in discovery phase via insights, frameworks, causal inference solutions and machine learning prototypes via POCs. 
• Refine standards and processes for AI solution development & implementation in close collaboration with data science leaders and team in the US. Ensure adherence to the industry / enterprise standards and best practices. 
• Develop and institutionalize best practices and re-usable components, contribute to research and experimentation efforts. 
• Lead, coach, support, and mentor data scientists in the team review their work as required, provide adequate guidance, feedback to help them achieve their goals and do right for Enterprise. 
• Participate in talent acquisition activities to build strong talent pool of Data Scientists. 

Providencene
Providence’s vision to create ‘Health for a Better World’ aids us to provide a fair and equitable workplace for all in our employment, whether temporary, part-time or full time, and to promote individuality and diversity of thought and background, and acknowledge its role in the organization’s success. This makes us committed towards equal employment opportunities, regardless of race, religion or belief, color, ancestry, disability, marital status, gender, sexual orientation, age, nationality, ethnic origin, pregnancy, or related needs, mental or sensory disability, HIV Status, or any other category protected by applicable law. In furtherance to our mission in building a more inclusive and equitable environment, we shall, from time to time, undertake programs to assist, uplift and empower underrepresented groups including but not limited to Women, PWD (Persons with Disabilities), LGTBQ+ (Lesbian, Gay, Transgender, Bisexual or Queer), Veterans and others. We strive to address all forms of discrimination or harassment and provide a safe and confidential process to report any misconduct.
Contact our Integrity hotline also, read our Code of Conduct.
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