Senior Manager

• Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
• Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions.
• Design and build technical processes to address business issues.
• Oversee the design and delivery of reports and insights that analyze business functions and key operations and performance metrics.
• Recruit, train, develop and supervise analyst-level employees.
• Developing machine learning models leveraging Gen AI, Deep learning, and algorithms
• 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 modeling, visualization, and communication deliverables.
• Examine, interpret, and report results of analytical initiatives to stakeholders in leadership, technology, sales, marketing, and product teams.
• Oversee the data/report requests process: tracking requests submitted, prioritization, approval, etc.
• Develop and implement quality controls and departmental standards to ensure quality standards, organizational expectations, and regulatory requirements.
• Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs.
• Organize and drive successful completion of data insight initiatives through effective management of analyst and data employees and effective collaboration with stakeholders.
• Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company.

• Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources.
• Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.
• Experience writing advanced Python code statements, models, and macros.
• Experience working with and creating databases and dashboards using all relevant data to inform decisions.
• Experience using analytics techniques to contribute to company growth efforts, increasing revenue and other key business outcomes.
• Strong problem solving, quantitative and analytical abilities.
• Strong ability to plan and manage numerous processes, people, and projects simultaneously.
• Excellent communication, collaboration, and delegation skills.
• We re looking for someone with at least 9-11 years of experience in a position monitoring, managing, manipulating, and drawing insights from data, and someone with at least 5+ years of experience leading a team.

The right candidate will also be proficient and experienced with the following tools/programs:

• Extensive experience with machine learning algorithms and ability to apply them in supervised and un-supervised settings such as NLP, classification, and predictive analytics
• Experience working with Gen-AI, expertise in fine-tuning transformer-based models / LLMs- GPT, Llama, PaLM, BERT and RAG models.
• Proven track record in developing and deploying AI models in the cloud and API integration for models
• Strong programming skills in languages such as Python, SQL, TensorFlow, PyTorch, Keras
• Over 3 years experience working with FHIR data and a good understanding of US healthcare
• Experience with Different databases (SQL, Cosmos DB, Snowflakes,) and handling Unstructured data.
• Experience with big data tools: Teradata, Big Hadoop, etc.
• Experience with data visualization tools: Qliksense, Power BI, Raw, chart.js, etc.
• Experience with Adobe Analytics and other analytics tools
• Experience with Excel, Word, and PowerPoint