24 days ago
Responsibilities
- Own analytical data products end to end, from data models and pipelines through metrics, models, and APIs.
- Apply statistical methods including experiment design, A/B testing, sample sizing, confidence intervals, significance testing, segmentation, drift checks, anomaly detection, reconciliation, and outlier handling.
- Build, evaluate, serve, and monitor classical machine learning models in production, including feature engineering and model-quality evaluation.
- Design and operate APIs, events, schemas, data contracts, and versioned data-serving interfaces for internal consumers.
- Build streaming and event-driven data flows for near-real-time and operational analytics.
- Design customer data models covering identity resolution, lineage, confidence, relationships, and data quality across multiple database and architectural patterns.
- Partner with product, architecture, data, security, privacy, and analytics teams to drive platform adoption.
- Mentor engineers and raise engineering and analytical standards across teams.
Requirements
- 10+ years of experience building APIs, backend services, and data-intensive platforms with measurable business or analytical outcomes.
- Applied statistics experience covering sampling, sample sizing, confidence intervals, hypothesis testing, base rates, data bias, and model-quality evaluation.
- Hands-on experience taking classical machine learning models into production from feature and training-data development through serving and drift monitoring.
- Strong Python and SQL skills with production Apache Spark experience.
- Experience building and operating APIs or backend services, including API design, schema evolution, and production service architecture.
- Experience with event-driven architecture, data contracts, and streaming or messaging platforms such as Kafka, Kinesis, or Flink.
- Deep understanding of data modeling, database design, schema evolution, identity resolution, data quality, and source-of-truth patterns.
- Ability to influence multiple teams, shape technical direction, and drive cross-functional outcomes.
- Preferred experience with Databricks, Delta Lake, Unity Catalog, Delta Live Tables, Node.js, TypeScript, large-scale machine learning model serving, Customer 360, customer data platforms, master data management, deterministic or probabilistic matching, confidence scoring, graph-based models, and privacy-sensitive or regulated data environments.
Benefits
- Full-time role based in Sterling, Virginia.
- Opportunity to define the data foundation, analytical standards, and serving layer for Asurion’s Customer 360 Platform.
- Asurion is committed to equal employment opportunity and building a diverse and inclusive workplace.
Tech Stack
Amazon DynamoDBApache FlinkApache KafkaApache SparkDatabricksElasticsearchMongoDBMySQLNeo4jNode.jsPostgreSQLPythonRedisSQLTypeScript
Categories
Data EngineeringML Engineering
About Asurion
As the world’s leading tech care company, Asurion eliminates the fears and frustrations associated with technology, to ensure our 300 million customers get the most out of their devices, appliances and connections. We provide insurance, repair, replacement, installation and 24/7 support for everything from cellphones to laptops and household appliances. Our experts are available online, on the phone, at one of our more than 800 stores, or can even come to you.