- Company Name
- Edison Smart®
- Job Title
- Senior Data Scientist - FinCrime
- Job Description
-
**Job Title:** Senior Data Scientist – FinCrime
**Role Summary:**
Design, develop, and deploy machine‑learning and AI solutions that support forecasting, anomaly detection, and fraud detection for a financial‑crime prevention program. Translate analytical insights into production‑ready models and integrate them into automated decision‑making workflows.
**Expectations:**
- 3–7+ years of professional experience in data science, machine‑learning engineering, or applied analytics.
- Strong proficiency in Python (Pandas, NumPy) and ML libraries (scikit‑learn, TensorFlow, Keras).
- Advanced SQL skills for data extraction, transformation, and analysis.
- Hands‑on experience with cloud platforms (AWS or Microsoft Azure).
- Demonstrated ability to move models from prototype to production, including CI/CD and MLOps practices.
- Excellent written and verbal communication for cross‑functional collaboration.
- U.S. citizenship or Green Card (eligible for 1099 contracting).
**Key Responsibilities:**
- Develop and validate forecasting, anomaly‑detection, and fraud‑detection models.
- Build end‑to‑end AI pipelines and integrate models into real‑time or batch production environments.
- Implement MLOps workflows: version control, automated testing, containerization, and monitoring.
- Conduct data preprocessing, feature engineering, and exploratory analysis using SQL and Python.
- Collaborate with business stakeholders to define problem statements, success metrics, and deployment requirements.
- Document model design, assumptions, performance metrics, and maintenance procedures.
- Provide technical guidance and mentorship to junior data scientists or analysts.
**Required Skills:**
- Python (Pandas, NumPy, scikit‑learn, TensorFlow/Keras)
- SQL query design and data manipulation
- Cloud services: AWS (SageMaker, EC2, S3) or Azure (ML Studio, Databricks)
- Model deployment tools: Docker, Kubernetes, CI/CD pipelines (Jenkins, GitHub Actions)
- Knowledge of MLOps principles and monitoring frameworks
- Statistical modeling, time‑series forecasting, anomaly detection, fraud detection techniques
- Strong problem‑solving and communication abilities
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field (Master’s preferred).
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Microsoft Azure AI Engineer, TensorFlow Developer) are advantageous but not mandatory.
New york city, United states
Hybrid
Senior
13-01-2026