Data Scientist

Who you are

• 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 practical experience
• Proficiency in at least one general-purpose programming language used in data science (Python, or Scala)
• Solid experience writing and optimizing SQL for large datasets; comfort working in data lake / warehouse environments
• Hands‑on experience with Spark or PySpark and common ML libraries (e.g., scikit‑learn, XGBoost, TensorFlow/PyTorch a plus)
• Familiarity with UNIX environments and the AWS ecosystem (e.g., EMR, S3); Databricks experience is a plus
• Working knowledge of supervised/unsupervised ML and basic statistics (similarity measures, clustering, evaluation metrics)
• Exposure to graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames) is a strong plus
• Bonus: experience with Elasticsearch or DynamoDB; workflow tools such as Airflow for automating data pipelines
• Ability to break down loosely defined problems, ask good clarifying questions, and iterate quickly with feedback

What the job involves

• The Big Data R&D team is responsible for building the core identity graph and entity-resolution capabilities that power Socure’s Deceased Monitoring and compliance products
• In this role, you will help develop graph-based algorithms and data pipelines on massive PII datasets, support modelers with high-quality features, and evaluate new data sources that feed our identity and fraud products
• You will work closely with senior data scientists and engineers while developing your skills in large-scale ML, distributed systems, and graph analytics
• Contribute to the design and implementation of machine learning, data mining, statistical, and graph-based algorithms to analyze very large datasets for identity verification and anomaly detection
• Analyze large datasets to help develop and refine entity-resolution and identity-matching algorithms that drive Socure’s Deceased Monitoring and compliance solutions
• Build and maintain components of data-processing pipelines (ETL, feature generation, normalization) using tools such as Spark/PySpark and AWS (e.g., EMR, S3)
• Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for new models and signals
• Help evaluate new third‑party and internal data sources: profile data quality, design offline experiments, and summarize impact on coverage and model performance
• Implement and maintain SQL and Python/R code for data extraction, transformation, and validation; contribute to code reviews and basic testing
• Provide analytical support to compliance and regulatory product teams, including ad hoc investigations, simple dashboards, and data deep dives
• Communicate findings in a clear, structured way to peers and cross‑functional partners (Product, Engineering, Client Analysis), focusing on key insights and trade‑offs
• Work effectively in a fast‑paced, cross‑functional environment; demonstrate ownership of well-scoped tasks and follow through to completion

Benefits

• Health: Comprehensive medical coverage, including vision, dental, and FSA
• Parental Leave: Generous leave allowance for parents-to-be
• 401k: Pre-tax savings for retirement
• Life Insurance: Protect your family in case of emergency
• PTO: Take as much time as you need, when you need it
• 100% Remote: Work from anywhere anytime, whatever suits your lifestyle
• WFH Allowance: Generous reimbursement program to maximize your WFH setup
• Deskpass: Work in an office environment whenever you feel the need
• Mental Health Provider: Connect with clinicians when you need it
• Learning & Development: Self-education allowance & free career coaching
• Employee Assistance Program "EAP": Lifestyle resources available as well as additional mental health resources
• Fertility Provider: Family planning solutions for those interested
• Personal Legal Support: Significant discounts with RocketLawyer