Salary
💰 $158,000 - $205,000 per year
Tech Stack
ETLMavenPandasPySparkScalaScikit-LearnSQL
About the role
- Senior technical role within Data Sciences; analytic project ownership from conceptualization to design.
- Oversee development, implementation and enhancement of analytically derived models in a high-volume data environment.
- Provide leadership and mentoring to junior analysts; manage and potentially hire/manage a team of data scientists.
- Participate in or lead design, development, and maintenance of models for assessing risk and detecting and preventing fraud.
- Design data ETL and storage schemes for complex datasets from various sources and manage analytic data processes.
- Support large scale business initiatives and prepare analytic design documentation; present technical information to management.
- Research and recommend new analytical techniques/software and train team members; support data integrity and confidentiality.
Requirements
- 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.
- 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.
- Proven experience with understanding business requirement and translating into an analytic design
- Strong ability to effectively communicate findings from complex analyses to non-technical audiences.
- Proven ability to evaluate different analytical approaches and select the optimal design and techniques.
- Capability to lead large scale analytic projects independently involving multiple analysts and partner with other departments
- Background and drug screen
Preferred qualifications:
- Advanced degree strongly preferred.
- Deep knowledge of advanced ML algorithms
- Experience using ML-related libraries, such as scikit-learn, pandas, etc.
- Experience in writing and tuning SQL.
- 2+ years experience working with financial data.