Early Warning is looking for a senior technical role within Data Sciences to oversee the design, development, implementation, and enhancement of analytically derived models and products in a high-volume, high-throughput data environment to assess risk and detect/prevent fraud.
Requirements
- Advanced experience in data mining, data manipulation and data step programming required using Pyspark, Scala and Hive.
- Advanced experience in designing and utilizing a wide variety of machine learning, predictive modeling, and optimization techniques.
- Extensive knowledge on commonly used, industry related analytical data sources
- Proven experience with understanding business requirement and translating into an analytic design.
- Proven ability to evaluate different analytical approaches and select the optimal design and techniques.
- Deep knowledge of advanced ML algorithms
- Experience using ML-related libraries, such as scikit-learn, pandas, etc.
Responsibilities
- Participate in or lead the design, development, and maintenance of analytically derived models for assessing risk and detecting and preventing fraud.
- Design data ETL and storage schemes for complex datasets from various sources.
- Play leading role in supporting large scale business initiatives.
- Preparation of analytic detail design documentation.
- Oversees documentation of analytic solutions developed
- Responsible for overall analytic data processes, designing and directing program development.
- Research and recommend new analytical techniques / software and train the team members accordingly.
Other
- Bachelor’s Degree in Mathematics, Statistics, or related field.
- A minimum of 10 years data analytics experience in a data rich environment (or equivalent education and experience).
- A minimum of 7 years experience in efficient programming enabling timely manipulation and analysis of large data sets.
- Strong ability to effectively communicate findings from complex analyses to non-technical audiences.
- Capability to lead large scale analytic projects independently involving multiple analysts and partner with other departments
