Trellance is a leading provider of business analytics and technology consulting for credit unions, helping them meet the financial needs of today’s digital consumer. With a comprehensive suite of data science solutions, professional staffing and professional services, the Trellance team ensures credit unions increase efficiency, manage risk, and improve member experience. As credit unions’ tech partner, Trellance brings them to the next frontiers of fintech, filled with powerful tools such as artificial intelligence and machine learning.
Primary focus is to apply data mining techniques, do statistical analysis, and build high quality prediction systems integrated with our products and services. Help our clients discover the information hidden in vast amounts of data to allow them to make smarter decisions to deliver even better products and services to their customers.
· Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
· Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
· Support the architecture team in the definition of the optimal architecture to collect, store and deliver insights from the combined datasets.
· Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy.
· Analyze data for trends and patterns and Interpret data.
· Implement analytical models into production by collaborating with software developers and machine learning engineers.
· Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.
· Select features, build and optimize classifiers using machine learning techniques.
· Data mining using state-of-the-art methods.
· Extend Trellance’s data with third party sources of information when needed.
· Enhance data collection procedures to include information that is relevant for building analytic systems.
· Process, cleanse, and verify the integrity of data used for analysis.
· Perform ad-hoc analysis and present results in a clear manner.
· Create automated anomaly detection systems and constant tracking of its performance.
· Other duties as assigned.
Bachelor’s degree (BA or BS) from an accredited college or university plus a minimum of four (4) years of experience in the specific or related field.
Company / Industry Knowledge:
Knowledge of financial institutions and financial data, preferably credit union or retail banking related a plus.
- 5+ years of experience in data science.
- Proficiency with data mining, mathematics, and statistical analysis.
- Advanced pattern recognition and predictive modeling experience.
- Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (i.e., Java/Python, SAS).
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc . Excellence in at least one of these is highly desirable.
- Great communication skills.
- Applied statistics skills, such as distributions, statistical testing, regression, etc.
- Scripting and programming skills.
- Prior consulting experience a plus
- Up to 20% travel may be required