Data Scientist

Xylem is a Fortune 500 global water solutions company dedicated to advancing sustainable impact and empowering the people who make water work every day. As a leading water technology company with 23000 employees operating in over 150 countries Xylem is at the forefront of addressing the worlds most critical water challenges. We invite passionate individuals to join our team dedicated to exceeding customer expectations through innovative and sustainable solutions.

What Youll Do (Responsibilities)

• Lead endtoend data science projects from scoping through deployment and monitoringcovering telemetrybased predictive models LLM agents and optimization of existing ML solutions.
• Translate business requirements from service operations product management and field teams into testable hypotheses features and measurable outcomes.
• Develop timeseries models (forecasting anomaly detection event prediction) using Python; design features from highvolume IoT data and join with ERP/CRM context.
• Build and productionize models in Azure: train/evaluate in Azure Machine Learning register/promote in the AML model registry and automate with Azure Data Factory/Databricks workflows.
• Engineer robust data connectors (e.g. SQL/pyodbc) to ERP telemetry stores and SharePoint/OneDrive sources; use service principals and managed identities for secure refreshes and pipelines.
• Design evaluate and ship LLM agents that use retrieval and tool invocation (e.g. RAG over ADLS/Power BI/Dynamics or SAP context) with responsibleAI guardrails in Azure AI Foundry.
• Instrument model performance & business impact (drift stability precision/recall lead time gain falsepositive cost) and partner with operations to drive adoption.
• Partner across WSS (DCC operations IoT software product and field service) on SAPintegrated and Link2Siteenabled workflows to ensure solutions are operable and auditable.
• Tell the story: build concise Power BI views/dashboards to explain models KPIs and value to stakeholders; create clear docs and runbooks.

Required Qualifications

• 3 years experience of applied data science in production environments preferably in IoT/industrial telemetry.
• Education (Required): Bachelors degree in Data Science Computer Science Statistics Applied Mathematics or a related quantitative field.
• Education Preferred: Masters degree or higher in a relevant discipline (e.g. Data Science AI/ML Industrial Analytics) or equivalent practical experience delivering production-grade ML solutions.
• Strong Python development experience; familiarity with PySpark a plus.
• Timeseries modeling expertise (forecasting anomaly detection state models survival/event prediction; e.g. ARIMA/Prophet gradient boosting LSTM/Temporal CNNs).
• Proficiency in SQL and pyodbc; schema design query optimization and joining telemetry with ERP/CRM data.
• Handson with Azure ML (training pipelines environments) AML model registry ADLS Gen2 Azure Data Factory Databricks.
• Practical MLOps: model versioning CI/CD orchestration monitoring and rollback strategies; Git/GitHub/Azure DevOps.
• Power BI for analytical storytelling and operational monitoring (rowlevel security dataflows refresh strategies; working knowledge of service principals is a plus).
• Demonstrated ability to translate functional requirements into models and measurement plans; strong stakeholder communication.

Preferred Qualifications

• Education (Preferred): Masters degree or higher in a relevant discipline (e.g. Data Science AI/ML Industrial Analytics) or equivalent practical experience delivering production-grade ML solutions.
• Experience building ML solutions within Databricks or Snowflake.
• Experience with LLM agent design (prompting tools RAG evaluation) in Azure AI Foundry; understanding of guardrails content filters and privacy.
• Experience with SAP S/4HANA objects relevant to service (orders maintenance plans) and integration patterns between IoT platforms (Link2Site) and ERP.
• Domain experience in predictive maintenance service order automation or consumables/exchange forecasting within industrial systems.

Example Problem Areas Youll Tackle

• Predictive models from IoT telemetry to anticipate failures/exchange events and generate proactive service actions; integrate with SAP/field workflows.
• LLM agents that unify knowledge from telemetry ERP and SharePoint/OneDrive docs to assist DCC analysts in triage and resolution (RAG tool use).
• Optimization of existing ML (feature engineering retraining cadence ruleplusmodel ensembles) to improve precision and reduce operational toil.
• Data health & identity: secure refreshes and managed identity patterns for analytics artifacts and pipelines.

Tech Stack Youll Use

Python SQL Azure ML AML Registry ADLS Gen2 Azure Data Factory Azure AI Foundry Databricks (PySpark) Miccrosoft Power BI/Fabric Git/Azure DevOps.

Join the global Xylem team to be a part of innovative technology solutions transforming water usage conservation and re-use. Our products impact public utilities industrial sectors residential areas and commercial buildings with a commitment to providing smart metering network technologies and advanced analytics for water electric and gas utilities. Partner with us in creating a world where water challenges are met with ingenuity and dedication; where we recognize the power of inclusion and belonging in driving innovation and allowing us to compete more effectively around the world.