Data Scientist

Schedule

Overview

This position is responsible for aiding operational areas of the organization leveraging both internal and external data assets to achieve business insights, gain deeper understanding of member needs, and enhance tactical and strategic decision making.

Responsibilities

Collaborates with business segments to extract analytical, behavioral and predictive insights from ever increasing data resources. Applies progressive statistical, programmatic, and analytical approaches to business hypotheses to gain deeper understanding of available data. Aids business owners in the interpretation of the results of models and analysis. Requires a solid understanding of both the technical and business aspects of Data Science and business analytics. Must be able to understand the analytical needs of business users, and the business, and translate those needs into actionable resources. Requires full Data Science life cycle development experience within various analytical architectures, including piloting models, A/B testing, underlying data design, and model operationalization. Models will be deployed using agile methodologies to ensure timely and relevant delivery.

Responsible for the design, development, and maintenance of analytical models that will be placed into operation. Will be required to explore internal and external data sources to identify useful structures within the data that were/are previously unknown to the business. Should have a strong understanding of relational and dimensional modeling to facilitate data wrangling, model operationalization, and exploration of data. Must have experience with R, Python, and Linux. Responsible for adhering to corporate reporting policy and controls to ensure the accuracy, timeliness and confidentiality of corporate data and reports. Must be able to work with users from all levels of management in developing and implement operational and strategic analytics. The Data Scientist’s primary focus will be performing data mining, statistical analysis, and operationalization of analytical models. This is not a research, proof of concept, or theorist position, the data scientist must be able to drive real business value.

ESSENTIAL FUNCTIONS AND BASIC DUTIES:

• Uncover and operationalize underlying structure within the data into tangible business value utilizing machine learning.
• Develop models, processes, and structures necessary to support analytic needs of America First Credit Union using machine learning in 4th generation and 3rd generation computer languages.
• Work with analytics information manager and other staff to implement various analytical models, anything from churn, future value, or recommender systems.
• Build small reporting layer on top of analytical models to ensure accountability and insight into models outcomes and impact.
• Able to pilot and build POC’s to demonstrate and test business value of model.
• Extracts operational, performance, statistical and other data from various information systems.

• Educate and demystify analytical models to business users.
• Develop presentations and trainings for business users to increase understanding of statistics and implementation of models.
• Maintain department as the competency center for analytics within America First Credit Union.

• Works closely with analytics information manager to interpret report results.
• Analyze, interpret, and summarize analytical model’s results.
• Participates in the interpretation and context of complex business reports.
• Runs what-­‐if simulations based on varying factors and assumptions.
• Identifies exceptions, positive and negative trends and measures that are out of tolerance with established limits and ranges.
• Identifies potential concerns based on projections of current trends.
• Performs statistical and financial analysis of data.

Qualifications

• Must have prior experience developing business analytical solutions in large or midsize companies.
• Must be able to manage multiple tasks simultaneously and react to problems quickly.
• Must be able to translate concepts and directions into practical solutions.
• Must have experience in reporting on business analytical solutions.
• Must have strong presentation skills.
• Must have programming experience with 4th generation and 3rd generation computer languages such as Python and R.
• Must have experience with Linux.
• Must have experience with data mining models, for example Linear Regression, Random Forest, Support Vector Machines…
• Must have development experience with relational database structures, multi-dimensional database, and data warehouse design architecture.
• Must have strong SQL abilities, experience with both Oracle and Microsoft desired.
• Must be able to develop, maintain, review and explain data models.
• Must have excellent verbal and written communication skills.
• Must be a team player.
• Must understand numerous references to all things nerdy.
• Understanding of the financial services industry desired.
• Experience with dashboard design and delivery.

EXPERIENCE:

• Three or more years of experience in designing, developing and implementing Data Science solutions.

EDUCATION:

• Masters of science in information technology, computer science, statistics, or related degree.
• Bachelors of sciencedegreeininformationtechnology,computerscience,statistics, or related business degree with equivalentexperienceof 3 years.