Data Scientist II - Big Data R&D, Identity Graph & Deceased Monitoring
The Data Scientist II role at Confidential Client focuses on developing advanced graph-based and machine learning algorithms to enhance identity verification and fraud detection capabilities, particularly for deceased monitoring and compliance products. The position involves working with large-scale PII datasets, building data pipelines using Spark and AWS, and collaborating closely with senior scientists and cross-functional teams to deliver impactful data-driven solutions in a fast-paced environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Artificial Intelligence.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
About the Role
Confidential Client is looking for a Data Scientist II to join a Big Data R&D team building core identity-graph and entity-resolution capabilities used in deceased monitoring and compliance products. In this hands-on role you will design and implement graph and statistical algorithms, build scalable data pipelines, and support modelers with high-quality features that improve identity-matching and fraud-detection systems.
What You’ll Do
- Contribute to design and implementation of machine learning, graph-based, and statistical algorithms to analyze very large PII datasets for identity verification and anomaly detection.
- Analyze large datasets to develop and refine entity-resolution and identity-matching algorithms powering deceased monitoring and compliance solutions.
- Build and maintain ETL and feature-generation pipelines using Spark/PySpark and AWS technologies (e.g., EMR, S3).
- Implement, review, and maintain SQL and Python/R code for data extraction, transformation, and validation.
- Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for model and signal evaluations.
- Evaluate new third-party and internal data sources: profile data quality, design offline experiments, and summarize impacts on coverage and model performance.
- Provide analytical support for compliance and regulatory product teams, including ad-hoc investigations and simple dashboards.
- Communicate findings clearly to peers and cross-functional partners (Product, Engineering, Client Analysis), focusing on key insights and trade-offs.
- Own well-scoped tasks end-to-end and work effectively in a fast-paced, cross-functional environment.
What You’ll Bring
- Master’s degree with 2+ years of experience, or Ph.D. with 1+ years of experience in a data science or analytics role, or equivalent experience.
- Proficiency in a general-purpose language used in data science (Python or Scala).
- Strong SQL skills and experience working with large datasets in data lake/warehouse environments.
- Hands-on experience with Spark or PySpark and common ML libraries (scikit-learn, XGBoost; TensorFlow/PyTorch a plus).
- Familiarity with UNIX environments and AWS (EMR, S3); Databricks experience is a plus.
- Working knowledge of supervised/unsupervised ML and statistics (similarity measures, clustering, evaluation metrics).
- Ability to break down loosely defined problems, ask clarifying questions, iterate quickly, and incorporate feedback.
Preferred / Nice-to-Have
- Experience with graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames).
- Experience with Elasticsearch or DynamoDB.
- Familiarity with workflow orchestration tools such as Airflow.
- Prior work on identity, entity resolution, or deceased monitoring fraud-detection systems.
Location & Eligibility
- This position is based in New York, NY. Applicants must be located within ~45 miles of a talent hub to be considered.
- Sponsorship for employment is not available at this time.
Compensation & Benefits
- Compensation range: $140,000 - $170,000 per year (base salary). Actual pay is determined by skills, experience, and location.
- Confidential Client offers benefits typical for data science roles at scale (medical, dental, vision, retirement, paid time off). Specific benefits will be shared during the hiring process.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
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