Interested in this Data Scientist role at WSECU?
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About This Role
Are you a talented Data Scientist? WSECU is looking for a Data Scientist to synthesize and leverage our many datasets in order to enhance the products and services we offer to make our members’ financial lives easier. You’ll be responsible for continually challenging our current best thinking on how our products and services are meeting our members’ financial needs.
This is a unique opportunity to join a new, multidisciplinary team of creative and passionate individuals determined to change the face of the Credit Union industry. We are focused on the Credit Unions agenda, and work on high\-impact projects utilizing big data analytics and machine learning to improve the financial well\-being of our members.
Your day might include:
- Working with end\-users and analysts to model complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, and visualization techniques
- Modeling and framing business scenarios that are meaningful and which have direct impact on critical business processes and / or decisions
- Interviewing end\-users to determine requirements for data, reports, analysis, and performance
- Helping build WSECU’s capability and strategy (short term and long term) to understand and assess new products, and evaluate the success of existing products and services
- Distilling insights from member data that address key business challenges and provide actionable recommendations
- Ability and desire to solve business problems, and to find patterns and insights within structured and unstructured data.
- Experience with Programming and/or scripting languages a plus. Python strongly preferred
- Developing \& communicating data insights \& recommendations in a clear \& concise manner (i.e., data driven change management)
- Providing expertise on mathematical concepts for the broader applied Analytics and Insights team and inspiring the adoption of advanced analytics and data science across the entire breadth of our organization
What you bring to the team:
- Master's Degree in one of the following areas: econometrics, operations research, applied statistics, machine learning, hard science or engineering, or related quantitative discipline
- Demonstrated understanding of the financial and economic levers that impact WSECU’s business performance
- Strong technical, analytical, and problem\-solving skills and the ability to effectively utilize techniques to derive insights
- Demonstrated ability to communicate operational and technical issues to a wide variety of audiences at all organizational levels – must have strong data storytelling abilities
- Expertise in one the following: econometric modeling; statistical and predictive modeling; machine\-learning approaches such as; clustering and classification techniques, recommendation and optimization algorithms
- well\-developed oral and written communication skills including the writing of executive and board level reports, human relation skills and problem\-solving skills
- Requires the ability to communicate effectively to many levels of staff internally as well as outside individuals and vendors outside the organization with the ability to present ideas in business\-friendly and user\-friendly language
Bonus points if you have:
- Postgraduate school experience delivering world\-class data science outcomes (2\+ years preferred)
Competitive base pay: $113,119\.47 \- $169,679\.21 annually, dependent on relevant qualifications, plus an annual discretionary incentive plan and benefits package
- *The target starting pay for this position is* $113,119\.47 *\- $141,399\.34 annually,* *typically within the* *first half of the range**. Actual offers will be based on individual qualifications relevant to the role and will not take an applicant’s pay history into account.*
- *The range above allows our employees room for growth through annual merit and other pay increase during their tenure in the position.*
Where we’re located: 330 Union Ave, Olympia WA. Employee must reside and perform all work in the state of Washington. This is a hybrid position that blends working in\-office and from home. Works onsite two (2\) occasions per week
When you’d work: Monday through Friday 8:30 am to 5:30 pm, full\-time minimum 40 hours per week, with scheduling flexibility to meet service needs for this *exempt* position.
Working from home/hybrid requirements:
- Reliable, high\-speed home internet connection
- Private, confidential workspace, away from distractions and other people
- Suitable desk/surface and desk chair
Perks: Here are a few benefits and perks we offer:
- Medical, Dental, Vision, and Life Insurance with Premiums options covered by WSECU
- Full\-Time Regular employees accrue general leave and sick leave, on a monthly basis
- Part\-Time employees accrue general leave, on a monthly basis
- 11 Paid Holidays
- Employer paid Long Term Disability \& Long\-Term Care plan for Full\-Time employees
- Employer paid Long Term Care plan for Part\-Time employees
- 401(K) with 8\.5% Contribution by WSECU to begin 1st quarter after 1 year of service
- Paid Volunteer Leave
- Tuition Assistance
- Employee Assistance Program \& Employee Discounts
- And, you get to work with some awesome people!
*WSECU was named to the Forbes Best\-In\-State Credit Union list in 2025, making us the* *only credit union in Washington* *to earn this recognition* *five years in a row**!*
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\#LI\-hybrid
We look forward to reviewing your application!
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All applicants must include a resume.
Visa sponsorship not available.
Contact us at 360\-754\-2118 with any questions.
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We champion our employees’ unique differences because we believe diversity is critical to the success of our members and the communities we serve. We’re proud to provide a workplace based on equality and do not discriminate based on race, color, religion, creed, national origin, ancestry, sex, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, marital status, or any other legally recognized protected basis under federal, state or local law.
Accommodations are available for applicants with disabilities. If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact 360\-754\-2118 or email us for assistance.
Salary Context
This $113K-$141K range is below the median for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At WSECU, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 789 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($127K) sits 34% below the category median. Disclosed range: $113K to $141K.
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.
WSECU AI Hiring
WSECU has 1 open AI role right now. They're hiring across Data Scientist. Based in Olympia, WA, US. Compensation range: $141K - $141K.
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 Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
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).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
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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