Senior Associate IS Bus Systems Analyst-Automation and Analytics

What you will do

In this vital role you will as a Senior Associate IS Business Systems Analyst with strong data science and analytics expertise to join the Digital Workplace Experience (DWX) Automation & Analytics product team. In this role, you will develop, maintain, and optimize machine learning models, forecasting tools, and operational dashboards that support strategic and day-to-day decisions for global digital workplace services.

This role is ideal for candidates with hands-on experience building predictive models and working with large operational datasets to uncover insights and deliver automation solutions. You will work alongside product owners, engineers, and service leads to deliver measurable business value using data-driven tools and techniques.

• Design, develop, and maintain predictive models, decision support tools, and dashboards using Python, R, SQL, Power BI, or similar platforms.
• Partner with delivery teams to embed data science outputs into business operations, focusing on improving efficiency, reliability, and end-user experience in Digital Workplace services.
• Build and automate data pipelines for data ingestion, cleansing, transformation, and model training using structured and unstructured datasets.
• Monitor, maintain, and tune models to ensure accuracy, interpretability, and sustained business impact.
• Support efforts to operationalize ML models by working with data engineers and platform teams on integration and automation.
• Conduct data exploration, hypothesis testing, and statistical analysis to identify optimization opportunities across services like endpoint health, service desk operations, mobile technology, and collaboration platforms.
• Provide ad hoc and recurring data-driven recommendations to improve automation performance, service delivery, and capacity forecasting.
• Develop reusable components, templates, and frameworks that support analytics and automation scalability across DWX.
• Collaborate with other data scientists, analysts, and developers to implement best practices in model development and lifecycle management.

We are all different, yet we all use our unique contributions to serve patients. The vital attribute professional we seek is with these qualifications.

Basic Qualifications:

• Master's degree Bachelor's degree and 5 to 9 years in Data Science, Computer Science, IT, or related field

• Data Science & ML: Proficient in Python (preferred) or R; experience with libraries such as scikit-learn, pandas, NumPy, XGBoost, and familiarity with TensorFlow or PyTorch. Skilled in supervised/unsupervised learning, time series forecasting, feature engineering, and hyperparameter tuning.
• SQL & Data Engineering: Advanced SQL (joins, CTEs, window functions, optimization) with experience in relational databases (PostgreSQL, SQL Server, Oracle, MySQL) and data modeling (star/snowflake schema).
• Databricks: Hands-on experience with Databricks notebooks (Python, SQL, PySpark), Delta Lake, MLflow, Unity Catalog, and Lakehouse architecture.
• Visualization: Power BI expertise (DAX, Power Query, data model optimization) and/or Tableau (advanced calculations, LODs, performance tuning).

• MLOps & Automation: Experience with Airflow, SageMaker, or Azure ML; knowledge of CI/CD for ML models and automated data pipelines.
• Generative AI: Understanding of foundation models (LLMs, transformers, diffusion); hands-on experience with APIs from OpenAI, Azure OpenAI, HuggingFace; prompt engineering for summarization, classification, Q&A, and content generation; bonus for fine-tuning, RAG pipelines, or vector databases (FAISS, Pinecone).
• Cloud Platforms: Familiarity with Azure (Data Factory, Synapse, Azure ML, Azure OpenAI), AWS (S3, Redshift, SageMaker), or GCP (BigQuery, Vertex AI).

• ITSM & Agile: Exposure to ITIL practices or ITSM platforms (e.g., ServiceNow) and working knowledge of Agile/SAFe environments

• Analytical mindset with attention to detail and data integrity
• Strong problem-solving and critical thinking skills
• Ability to work independently and drive tasks to completion
• Strong collaboration and teamwork skills
• Adaptability in a fast-paced, evolving environment
• Clear and concise documentation habits