Senior Data Science Engineer
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Job Description
Senior Data Science Engineer building LLM and classical ML risk-detection systems for LegitScript’s safer internet and payment platform. Owning data pipelines, production deployment, and model business impact.
Responsibilities:
- Own the full lifecycle from raw data ingestion to model deployment and measuring real-world business impact
- Research, prototype, and develop ML and LLM-based models for complex business problems, focusing on risk detection and prioritization
- Wrap models into production-ready APIs and integrate them into the core SaaS product
- Ensure model outputs are interpretable by translating predictions into actionable reason codes
- Partner with operational teams to gather feedback, refine features, and improve model relevance
- Design, build, and maintain scalable pipelines ingesting data from disparate sources into the data warehouse/lake
- Implement data validation, quality checks, and transformation workflows across raw, curated, and serving layers
- Build and maintain curated datasets for analytics and model training
- Implement and maintain CI/CD pipelines for data workflows and ML model deployment
- Monitor pipeline latency, data drift, and model performance; design alerting and retraining triggers
- Define success metrics, track ROI, and iterate models based on real-world efficacy
- Manage infrastructure as code and containerized deployments for reproducible releases
Requirements:
- 5–8+ years spanning data engineering and data science/ML, with a demonstrated track record of shipping models to production
- Strong Python proficiency
- Experience with Spark/PySpark for large-scale data processing
- Advanced SQL for complex transformation, analysis, and data modeling
- Hands-on experience with cloud data platforms such as Databricks or Snowflake
- Experience with ETL/ELT frameworks — dbt, Lakeflow Declarative Pipelines, Databricks Autoloader, Informatica, or similar
- Familiarity with ML experiment tracking tools such as MLflow or Weights & Biases
- DevOps fluency: Git-based development, branching strategies, CI/CD, IaC (DABs/Terraform), and Docker
- Experience with orchestration tools such as Databricks Workflows or Apache Airflow
- Strong plus: hands-on experience with LLMs and Generative AI techniques in a production context (prompt engineering, RAG architectures, fine-tuning, or evaluation frameworks)
- Strong plus: experience building or operating ML platforms, feature stores, or model registries
- Strong plus: prior work in risk, compliance, fraud detection, or other high-stakes ML domains
- Visa sponsorship is not available for this position
- International remote work is not supported
Benefits:
- Competitive compensation
- Flexible work options
- Team genuinely invested in your success
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