CO-OP Financial Services is bringing digital transformation to the credit union movement. We're creating innovative technology solutions that help not-for-profit credit unions best serve their members and compete with the big banks. As a result, our world-class team is growing faster than ever! If you're passionate about technology and want to be part of a purpose-driven organization, this is an exciting opportunity to provide real value and help shape the future of human-centered financial services.
We are seeking a talented Data Scientist to provide guidance to the business through informational insights taken from vast amounts of data. These insights will then further enable the business to make smarter decisions. The Data Scientist applies data mining techniques, mathematical and statistical analysis, and machine learning algorithms to large data sets in order to provide solutions for product and process optimization and further, tests the effectiveness of different scenarios to help determine the best course of action.What You Can Look Forward to
- Collaborates with stakeholders throughout the business to understand existing processes and identify opportunities for leveraging data to drive solutions.
- Communicates with CO-OP stakeholders at all levels including senior level executives and clients regarding CO-OP's reporting strategy, solutions and roadmap.
- Performs data mining and analysis from a variety of databases to help build solutions for optimizing product development, client card portfolios, and business and operational strategies.
- Designs and builds custom AI driven data models and algorithms applied to data sets to further optimize products and processes.
- Performs exploratory data analysis to determine effectiveness and accuracy of data to be applied to models and algorithms as well as accuracy of new data sources.
- Develops and performs A/B testing framework to determine model quality and validity.
- Interprets data analysis, model and algorithm results to business and technical teams to facilitate decisions.
- Coordinates with business and technical teams to implement models and provide monitoring and feedback to business of results.
- Designs and builds predictive modeling to increase and optimize credit union card portfolios, generate revenue opportunities, prevent client attrition, optimize portfolio segmentations for right-time offers, and other business outcomes.
- Develops processes and tools to monitor and analyze model performance and data accuracy.
- Follows industry standards and advances on data driven technologies and tools and further recommend those that will help further advance CO-OP's data science practice.
- Actively supports our CO-OP culture and embraces our core values of Work as Partners, Communicate Openly and Honestly, Demonstrate Excellence and Champion Change in all interactions.
- BS or MBA in Statistics, Mathematics, Computer Science, Advanced Analytics, or Data Mining. Specific data science or advanced analytics certificates combined with experience may be substituted.
- 5+ year's professional experience working within the business intelligence or data science field with experience in development of advanced analytics.
- Experience and skills in data mining, data analysis, data tools, design, build and implementation of models, algorithms as well as creating, running and interpretation of simulations.
- Experience using web services for data science such as Azure, AWS, Google or Redshift.
- Solid experience with R and other data science toolkits and supporting MPP data engines such as GreenPlum.
- Knowledge and experience using statistical computer languages to manipulate data, develop insights from large data sets and make recommendations on actions. Languages such as R, Python and SQL are essential.
- Experience in procedural languages such as C, C++, Java, and MATLAB.
- Knowledgeable of different machine learning techniques such as clustering, decision tree learning, Naïve Bayes, artificial neural networks, supervised classification and knowing when to apply each, their advantages and drawbacks.
- Proficiency with advanced statistical techniques such as various regression modeling (linear, logistic, polynomial, etc.), various forecasting methods, distribution properties and experience with applications.
- General knowledge of various data mining techniques such as tracking patterns, classification, association, outlier, clustering, regression and prediction for examples.
- Solid knowledge and experience with data visualization tools such as Power BI, Tableau, GGPlot and presenting for stakeholders.
- Proficiency with distributed/computing data tools such as Map/Reduce, Hadoop, Hive and Spark.
- Proficiency with various types of NoSQL databases (document, column, graph, key-value stores, etc.).
- Knowledge of analyzing data from 3rd party providers and further combining with other data sources to draw inferences, correlations, clusters and or scenario analysis.
- General knowledge of PCI standards and regulations.
- General knowledge and experience working within an agile environment.
- General knowledge of MS office tools Word, Excel, PowerPoint, Visio and Outlook.
- Strong problem solving skills with an emphasis on consumer back-office tools and product development.
- Good verbal, written and graphic communication skills. Ability to tell a story with data and data visualizations.
- Solid understanding of machine learning techniques and algorithms.
- Detailed-oriented in data validation, A/B testing, and monitoring of model or algorithm results.
- Ability to be skeptical of findings, correlations, assumptions and overall conclusions to ensure proper analysis and evaluation is done prior to submission to stakeholders.
- Innovative with the ability to leverage data to produce offerings that solve for inefficiencies and distinguish product offerings.
- Ability and willingness to consult with business stakeholders, interpret findings and make recommendations to aid decision making.
- Ability to troubleshoot data integrity issues involving multiple data sources including 3rd party data, and further analyze data for validity and completeness.
- Excellent communication skills and ability to translate the complex to simple and easier terms for business leaders and users of data.
- Ability to communicate to a wide audience including business and technical teams, high-level executives and clients.
- Passion for problem solving, sharing knowledge and continuous learning.
Get ready to be part of the exciting, ever-evolving and growing credit union movement! As a CO-OP employee, you'll have a chance to directly impact the access of financial opportunities to individuals and communities – and you'll help drive the future of fintech at an energetic organization where contributions are valued, and innovation is championed.
With more than 35 years of industry leadership, CO-OP Financial Services is the largest, most comprehensive credit union service organization in the nation. CO-OP serves as THE credit union technology engine, bringing payments solutions, engagement services and strategic counsel to help credit unions optimize member experiences to consistently provide seamless, personalized multi-channel offerings, while delivering secure, sophisticated fraud mitigation service.
CO-OP serves more than 3,000 client credit unions, with 60 million debit and credit cardholders, nearly 30,000 surcharge-free ATMs and more than 5,600 shared branches nationwide. Our vast technological ecosystem facilitates more than 6.5 billion transactions every year and equips credit unions of all sizes to deepen member engagement and prosper in the fast-paced world of fintech.
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