Data Scientist-Hybrid

The Data Scientist applies analytical techniques and methods to gain critical predictive insights into all areas of the business. Promotes analytics as a crucial value driver and source of competitive advantage, operational efficiency, and innovation. Takes unstructured business questions and skillfully creates actionable analytics solutions. Seeks not only to apply sophisticated analytical methods but recognizes the pros and cons of simplicity versus complexity, placing value on understanding the best approach. Presents results to technical and non-technical audiences and tells a compelling story using data.

Educates stakeholders in understanding the power and value of an analytical approach to decision-making; provides them with insights that contribute to the strategic goals of the organization and influence the decision-making process.
• Acts as a resource for Automated Machine Learning efforts; works with leadership, subject matter experts, and analysts to generate compelling and practical use cases, develops suitable models, assists in implementation efforts, and presents insights.
• Curates and pulls together data sets using database queries.
• Ability to create ETL pipeline jobs to automate Machine Learning models.
• Merges, explores, and analyzes large-scale datasets to find actionable business insight, seeking to understand the credit union business and its opportunities.
• Use descriptive and inferential statistics to perform advanced analysis.
• Transfers machine learning output into an insightful story using visualization tools.
• Creates predictive models, segmentation, and forecasting time series models as part of broader analytic inquiries.
• Supports the operationalization and integration of analytics outputs to achieve maximum business value.
• Assists with the cleansing, validation, testing, and troubleshooting of new and existing data sources.
• Assists with the creation and maintenance of documentation (e.g., runbooks) of machine learning model pipeline jobs.

Education

• Min/Preferred: Preferred
• Education Level: 4 Year / Bachelors Degree
• Description: Bachelors Degree or equivalent experience in a quantitative field such as Economics, Business/Marketing, and/or Operations Research.

Experience

• Minimum Years of Experience: 3
• Preferred Years of Experience: 5
• Comments: 3-5 years in quantitative analysis with demonstrated experience using statistical, econometric, machine learning, or data mining techniques.

Knowledge, Skills & Ability

• Experience with SQL, Excel, R/SAS/Python and other statistical analysis tools.
• Must have a balance of technical skills, change control process management, highly developed analytical and problem-solving skills, and a proven ability to manage and prioritize projects across multiple cross-functional teams.
• Superior verbal & written communication skills and be able to translate business questions into actionable insights as well as to champion data-based decision-making.
• Must have an appreciation and basic understanding of Data Governance and Data Management concepts.
• Results and goal-oriented self-starter with demonstrated leadership qualities.
• Strong familiarity with sources of data & a strong technology background.
• Must be resourceful and have strong organizational and planning skills.
• Must be able to work well within a team.
• Proficiency with the Microsoft suite of office products.
• Experience with business intelligence and data visualization tools such as Tableau or Power BI is highly preferred.
• Experience with financial systems as well as an understanding of Banking and Credit Unions is a plus.
• Experience with SCRUM or Sprint methodologies preferred.

Disclaimer

Logix Federal Credit Union is an equal opportunity employer that does not discriminate in employment opportunities or practices on the basis of race, religion, color, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other status protected by law.