Data Scientist II

Overview: Recognized by Clarivate, Forbes, the Human Rights Campaign, and Military Friendly® for innovation, workplace excellence, inclusion, and veteran support. A global building automation and industrial technology company with 100+ years of history, 25,000+ patents, and 7,000+ engineers, operating across 70+ countries and 4 major business areas. Its technologies support industries including buildings, manufacturing, healthcare, data centers, and utilities worldwide.

Benefits: 401(k) match: Employer matches 87.5% of the first 8% of eligible pay, up to 7% of base salary; generally fully vested after 3 years. Education support: Up to $5,250/year for eligible undergraduate programs and $7,500/year for graduate programs. Paid parental leave: 8 weeks (40 business days) for birth, adoption, or foster-care placement.

Paid time off: 56 hours of paid sick time annually, plus vacation and 12 paid holidays. Health coverage: Medical, dental, and vision plans, including an HSA-eligible medical option and 100% in-network preventive care.

HSA & FSA: Tax-advantaged accounts for eligible healthcare, dental, vision, and dependent-care expenses. Disability coverage: Short-Term Disability provides 100% of base pay for up to 8 weeks, then 70% through week 26; Long-Term Disability provides 60% of base pay after Short-Term Disability. Employee support: Company-paid with 8 sessions per issue per year, plus health and wellness resources. Employee support: Company-paid Employee Assistance Program with 8 sessions per issue per year, plus health and wellness resources. Insurance & discounts: Company-paid basic life insurance of 1× annual base pay, Accidental Death & Dismemberment coverage, Business Travel Accident Insurance, and employee discounts. Benefits may vary by location, position, employee classification, and eligibility.

Qualifications: 5+ years of experience in data science, audit analytics, risk analytics, fraud analytics, or a related field.3+ years of experience developing and implementing predictive or machine learning models, including classification, regression, anomaly detection, or risk scoring.3+ years of experience developing data pipelines, ETL processes, business intelligence/data visualization or data warehouse solutions using technologies such as PowerBI, Snowflake, Databricks, or Spark.3+ years of experience applying data analytics to Enterprise Risk Management, business, risk, audit, compliance, cybersecurity, or fraud-related problems.

Responsibilities: Lead audit analytics initiatives aligned with SOX, GDPR, NIST, and PCI DSS frameworks, including scoping, probabilistic modeling, testing, and reporting. Design, develop, and maintain robust ETL pipelines and data warehouses using Snowflake and Databricks. Design, develop, and maintain enterprise risk and fraud analytics models focusing on KRIs, risk scoring, anomaly detection, and fraud prevention while leveraging data visualization tools, such as PowerBI.Build and optimize predictive models for classification and regression tasks. Utilize SHAP and LIME techniques to interpret and explain model predictions.