Senior Data Science Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $160k - $175k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 0%

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LegitScript

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2007

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

LegitScript is a company that provides a merchant and market intelligence platform powered by artificial intelligence, primarily serving internet platforms, e-commerce marketplaces, and payments companies. The company specializes in evaluating, mitigating, and managing third-party risk with real-time monitoring and compliance solutions. LegitScript offers products such as Xray for merchant risk intelligence, marketplace and ad monitoring, and several certification services, including addiction treatment, healthcare, and CBD certification. It partners with major platforms like Google, Amazon, and Microsoft, and collaborates with companies such as White Bullet to enhance its monitoring capabilities. LegitScript aims to ensure safety and transparency for the commercial internet through its comprehensive risk assessment and compliance tools.

📋 Description

• 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