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About This Role
Job Overview
PenFed is hiring a (Hybrid) Senior Manager, Decision Science at our Tysons, Virginia location. This role leads the NPV modeling function within the Decision Science department. The incumbent will manage a team of data scientists to develop, maintain, and enhance NPV models for consumer banking products, including Auto Loan, Personal Loan, Credit Card, and Deposit. This role is also responsible for building out Customer Life Time Value (CLTV) modeling to drive member profitability. Throughout the model lifecycle, the incumbent will partner with Finance, Product Strategy, Credit Risk, Pricing, and Second Line stakeholders to validate key assumptions, ensure NPV results are updated and reviewed in a timely manner, support strategic business decisions, and maintain rigorous monitoring and reporting of model performance.
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 leadership and management in developing and implementing programs, policies, and procedures to ensure mission and core values are implemented.
- Collaborate with key stakeholders and set up agenda, which aligns with overall business strategic goal.
- Creatively leverage various statistical methodologies to solve business challenges.
- Develop and implement acquisition pricing and credit underwriting models to support lending decisions. Use advanced modeling and simulation techniques to optimize the performance of loan products and operations.
- Develop statistical models and scorecards for credit underwriting, loan pricing, collection, and portfolio risk monitoring.
- Collaborate with product managers to optimize marketing campaigns in acquisitions that align with the credit policies and scoring models.
- Develop price elasticity models to support risk adjusted pricing, as well as subsequently establish and maintain model governance.
- Monitor performance of quantitative models and support independent model validation efforts in accordance with the model governance policy.
- Participate in identification, measurement, and monitoring of credit risk as it relates to Merger and Acquisition (M\&A), loan purchases and participation, and other new business strategies.
- Utilize credit models and analytics to assist lending with policies and strategies that maximize profits and asset growth and minimizes credit and operating losses as well as other risk exposures.
Qualifications
Equivalent combination of education and experience is considered.
- Master's Degree in quantitative discipline is required. PHD is highly preferred.
- Minimum of ten (10\) years of related work experience in building statistical models and advanced data analysis.
- Minimum of two (2\) years of direct management experience required.
- Applied experience with NPV, Logistic Regression, Linear Regression, Machine Leaning, and Survival Analysis required.
- Advanced programming skills to include knowledge of statistical programs (e.g. SQL, Python, and R) required.
- Experience in building risk, revenue and targeting models for consumer products is required.
- 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.
- Detail oriented, results driven, and the ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.
- Critical thinking using both analytical and tactical approach to problem solving within the Quantitative Modeling team is required.
- Ability to interact effectively with team members across the management team, Lines of Business (LOB), credit officers, finance, model governance, oversight, validation, and audit organizations.
- Proven project management skills.
- Excellent oral and written communication skills required.
- Experience using A.I. tools preferred.
Supervisory Responsibility
This position will supervise employees.
Licenses and Certifications
There are no additional certifications 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 is required.
Pay Transparency
The anticipated starting salary range for this role is $97,400\.00 \- $224,184\.00
This position is eligible for an organizational performance based annual bonus, subject to board discretion and approval.
This position is eligible for an individual performance based annual bonus.
\#LI\-Hybrid
Benefits
At PenFed, we offer a robust benefits package designed to support you both personally and professionally. You'll have access to comprehensive health, dental, and vision plans; paid time off; and family\-friendly benefits like paid parental leave, care support, and fitness center access. Financial wellness is encouraged through features like a 401(k) match, employee loan discounts, and fully paid life and disability coverage. We also support growth via education assistance, community involvement, and volunteer opportunities.
Our Purpose
Helping members achieve their dreams since 1935\. Pentagon Federal Credit Union (PenFed) is one of America's largest federal credit unions, serving 2\.8 million members worldwide with $29 billion in assets. PenFed offers market\-leading certificates, checking and savings, credit cards, personal loans, mortgages, auto loans, and a wide range of other financial services, always with members' interests in mind. PenFed is federally insured by the NCUA and is an Equal Housing Lender.
Berkshire Hathaway HomeServices PenFed Realty, LLC is a full\-service real estate company ready to assist our clients with buying, selling and renting a home. The company is a wholly owned subsidiary of PenFed Credit Union and is the largest independently\-owned brokerage in the Berkshire Hathaway HomeServices network, placing us in the top 1% of all real estate brokerages in the country. With almost 60 offices and nearly 2,000 world\-class sales professionals, we offer complete service coverage in Virginia, Maryland, the District of Columbia, Delaware, Pennsylvania, West Virginia, Florida, Tennessee, Kansas and Texas. In addition, we also offer specialized client services which include management of vacation properties and long\-term rentals, corporate relocation services and national referral network.
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 [email protected] .
Salary Context
This $97K-$224K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At PenFed Credit Union, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($160K) sits 25% below the category median. Disclosed range: $97K to $224K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
PenFed Credit Union AI Hiring
PenFed Credit Union has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in McLean, VA, US. Compensation range: $161K - $440K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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