Senior Data Scientist, Enterprise Data Delivery

Company:  PenFed Credit Union
Location: McLean
Closing Date: 21/10/2024
Salary: £200 - £250 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description
Overview

Are you looking to take your career from good to great? As an employee of PenFed, every day is an opportunity to thrive, and be part of a team working to ensure our organization is providing world class service to our members, employees, and our communities. We exist to help our members realize their full potential, educate and encourage their dreams, and make every effort to follow our mission and help our members “do better.” Joining PenFed is more than being an employee; it’s about being a part of the PenFed family.

PenFed is hiring a (Hybrid) Senior Data Scientist, Enterprise Data Delivery at our Tysons, Virginia or San Antonio, Texas location. The primary purpose of this job is to develop and implement advanced analytics solutions and processes to drive business value. As a lead level professional on the Enterprise Data Team, this job develops, reviews, validates, and designs advanced analytics, AI/ML, and analytical model solutions. This role will drive key projects on their own and will work as the subject matter expert collaborating closely with cross-functional teams to provide guidance and leverage data analytics to unlock new opportunities, reduce expenses, and drive business value.


Responsibilities

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is not intended to be an all-inclusive list of job duties and the position will perform other duties as assigned.

  • Provide expert guidance to the team on complex business problems, offering strategic insights and recommendations for advanced analytics solutions including analytics models and AI/ML solutions.
  • Conduct autonomous end-to-end more complex statistical model creation, including but not limited to identifying objectives, compiling data, sampling/prepping data, feature selection, model comparison/selection, deployment, and monitoring. Ensure adequate internal control processes around model development, implementation, and validation are established.
  • Partner with other competency leads/developers, Data scientists, Data Analysts, Data stewards and support project planning, technical design, development, and solution deployment functions.
  • Provide guidance and mentorship to junior team members involved in major team projects such as model development and model validation.
  • Establish consistent and robust model implementation processes across models with effective review and controls.
  • Lead the development, monitoring, and maintenance of advanced risk models using cutting-edge machine learning and statistical methods, proactively researching and recommending innovative approaches to enhance model performance and accuracy.
  • Establish standardized documentation processes and consistent model implementation practices across the team, fostering collaboration with stakeholders to enhance model implementation processes and ensure seamless integration into forecasting tools.
  • Collaborate with IT and data engineering teams to ensure efficient data management, data quality, and data integration for analytics projects.
  • Foster a culture of data-driven decision-making and promote the use of advanced analytics across the organization.
  • Communicate effectively with senior management, regulators, internal audit, and other stakeholders regarding model development and implementation, demonstrating strong interpersonal skills and the ability to convey complex concepts clearly and concisely.
  • Participate in regular interactions with stakeholders to improve model implementation processes, integrating feedback and requirements into forecasting tools for effective utilization and optimal performance.
  • Partner with cross-functional teams to continually improve data governance, data quality, and data security in a multi-tenant environment; standardize data.

Qualifications

Equivalent combination of education and experience is considered.

  • Ph.D. or Master's Degree in a quantitative discipline, with a strong emphasis on advanced statistical modeling, machine learning, or data science.
  • Minimum of four (4) years of related work experience in building statistical models and advanced data analysis.
  • Proficiency in a broad range of advanced statistical techniques, including but not limited to Logistic Regression, Linear Regression, Time Series Analysis, Decision Trees, Cluster Analysis, Gradient Boosting Machine, and other machine learning algorithms required.
  • Advanced programming skills, with demonstrated proficiency in statistical programming languages such as SQL, SAS, Python, and R, as well as experience in leveraging advanced analytics tools and platforms.
  • Ability to manage multiple projects simultaneously and implement rapid changes in project direction.
  • Demonstrate strong data analysis skills, ability to understand underlying data and complex loss/balance forecasting models, various product features, possess organizational and prioritization skills, as well as strong attention to detail.
  • Critical thinking using both analytical and tactical approach to problem solving within the Quantitative Modeling team.
  • Professional demeanor and the ability to interact effectively with team members, senior management, credit officers, finance professionals, regulators, and other stakeholders, fostering collaborative relationships and driving consensus on key initiatives.
  • Work experience using ETL tool is a plus.
  • 1+ years Experience using cloud-native tool like AWS S3 and Snowflake.
  • Excellent oral and written communication skills required.

Work Environment

While performing the duties of this job, the employee is regularly exposed to an indoor office setting with moderate noise.

*Most roles require working in an office setting with moderate noise and the ability to lift 25 pounds.*

Travel

Ability to travel to various worksites and be on-call may be required.


About Us

Established in 1935, PenFed today is one of the country’s strongest and most stable financial institutions with over 2.8 million members and over $36 billion in assets. We serve members in all 50 states and the District of Columbia, as well as in Guam, Puerto Rico and Okinawa. We are federally insured by NCUA and we are an Equal Housing Lender. We are available to members worldwide, via the web, seven days a week, twenty-four hours a day.

We provide our employees with a lucrative benefits package including robust medical, dental and vision plan options, plenty of paid time off, 401k with employer match, on-site fitness facilities at our larger locations, and more.


Equal Employment Opportunity

PenFed management will maintain and observe personnel policies which will not discriminate or permit harassment or retaliation against a person because of race, color, creed, age, sex, gender, gender identity, gender expression, religion, national origin, ancestry, marital status, military or veteran status or obligation, the presence of a physical and/or mental disability or medical condition, genetic information, sexual orientation, and all statuses protected by applicable state or local law in all recruiting, hiring, training, compensation, overtime, position classifications, work assignments, facilities, promotions, transfers, employee treatment, and in all other terms and conditions of employment. PenFed will also prohibit retaliation against individuals for raising a complaint of discrimination or harassment or participating in an investigation of same.

PenFed will also reasonably accommodate qualified individuals with a disability so that they can apply for a job or perform the essential functions of a job unless doing so causes a direct threat to these individuals or others in the workplace and the threat cannot be eliminated by reasonable accommodation or if the accommodation creates an undue hardship to PenFed. Contact human resources (HR) with any questions or requests for accommodation at 402-639-8568.

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