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Job Overview
JOB DETAILS
Responsibilities:
- Role focuses on leveraging advanced analytics and ML to detect fraudulent activities across the insurance lifecycle and recommend interventions
- Develop fraud scoring systems to rank and prioritize problematic cases
- Listen to customer requirements and internal requests, query various data sources, mine data for insights, package and present results in a way that makes a recommendation or provides value for a customer
- Support the creation and maintenance of models in our predictive analytics ecosystem
- Assist senior data scientists and engineers in automating the movement and processing of data in a real-time and batch Machine Learning environment.
- Work with our Account Management team to standardize and productize valuable customer solutions
Qualifications:
- 4 year computer science or related degree (highly recommended, but may be waived with relevant experience)
- 5+ years of experience in data analytics or data science working primarily with cloud technologies at a reputable company with references (Insurance or Financial Services experience a plus)
- 3+ years of experience developing and implementing fraud solutions such as Account Opening Fraud, Enrollment Fraud, BOT detection, and data harvesting
- Strong mathematics and problem-solving skills
- Comfort communicating and presenting results to stakeholders and customers
- 5+ years experience using Python; experience using tools such as Jupyter Notebooks, Airflow, Spark, Hadoop/EMR, Sagemaker, S3, Glue, etc. a plus
- 5+ years of experience using SQL to analyze and combine data across a variety of sources
- Expertise interacting with multiple data storage types and products, such as S3, Postgres, Snowflake, HDFS, etc.
- Strong knowledge of of ML frameworks including xgboost and scikit-learn
- Expertise in statistical modeling and anomaly detection
- Self-motivated, proactive, organized and a willingness to learn (and be taught)
- You’re comfortable in a fast-paced, unstructured environment
- Eagerness to wear multiple hats and lend a hand to your teammates when called upon
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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