Data Scientist II

Job Description

Job Description

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.

• 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.

• 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.

• 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.