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Data Scientist – AI & Machine Learning Systems (Dublin, CA)

Confidential

Dublin, California Hybrid permanent

Posted: February 25, 2026

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Quick Summary

We are looking for a Data Scientist to join our team in Dublin, CA, to develop and implement AI & Machine Learning solutions for our credit score and personal finance platform.

Job Description

Data Scientist – AI & Machine Learning Systems (Dublin, CA)

**In order to have your application considered, you must complete every question on this application

SavvyMoney is a leading San Francisco East Bay fintech company.  We provide integrated credit score and personal finance solutions to 1,600 + bank and credit union partners nationally.  The SavvyMoney solutions integrate with more than 43 digital banking platforms.

SavvyMoney was recently recognized by the San Francisco Business Times and the Silicon Valley Journal as one of the "Top 25 Places to Work in the San Francisco Bay Area" and is an Inc. 5000 Fastest Growing Company.

We’re headquartered in Dublin, CA, and offer a flexible hybrid work environment that blends in-office collaboration with the freedom of remote work.

We are seeking a Data Scientist with strong Machine Learning Engineering capabilities to lead initiatives in predictive modeling, personalization, and AI-driven financial recommendations.

This role goes beyond traditional model development. You will work on adapting and deploying base models, integrating LLMs and building scalable AI systems. The goal is to power personalized marketing, loan offers, credit improvement strategies, next-best-action recommendations, and intelligent analytics experiences. You will collaborate closely with product and business teams to ideate and partner with engineering to deploy models into scalable, low-latency production environments.

Responsibilities

Perform exploratory analysis to identify high-impact opportunities for AI-driven optimization and automation.

Design, build, fine-tune, and deploy machine learning models for:

Marketing propensity modeling

Personalized loan offers and recommendations

Next-best-action and engagement optimization

Credit improvement and financial health predictions

Adapt and fine-tune foundation models and LLMs for domain-specific use cases including recommendation engines, intelligent copilots, and conversational insights

Partner closely with engineering teams to productionize models with strong considerations for latency, monitoring, reliability, and cost efficiency.

Help engineering build reusable ML frameworks, feature pipelines, and experimentation infrastructure to accelerate AI innovation.

Contribute to experimentation design (A/B testing, uplift modeling, bandits) to measure real business impact.

Work cross-functionally with Product and Business stakeholders to translate AI capabilities into measurable outcomes.

Implement model monitoring, drift detection, and performance tracking to ensure long-term reliability.

Follow responsible AI practices, ensuring fairness, transparency, and appropriate governance.

Experience 

Master’s or PhD in Computer Science, Statistics, Data Science, or related field (or equivalent experience)

6+ years of professional experience in data science or machine learning, ideally in fintech, financial services, or a B2B2C environment

Strong proficiency in SQL and Python (pandas, scikit-learn, PyTorch, TensorFlow, XGBoost, etc.)

Hands-on experience with tree-based models (XGBoost, LightGBM, CatBoost) and neural networks

Proficiency in notebooks (Jupyter, Colab, etc.) and deep learning frameworks such as TensorFlow and PyTorch for model development

Familiarity with LLMs and generative AI frameworks (HuggingFace, LangChain, OpenAI APIs, etc.) 

Experience deploying machine learning models into production environments with considerations for scalability and latency

Strong business acumen with the ability to translate complex analytical outputs into actionable recommendations

Excellent communication skills to collaborate with both technical and non-technical stakeholders

Preferred Experience 

Experience with cloud-based platforms (AWS, GCP, or Azure) for model training and deployment

Knowledge of MLOps tools and practices (MLflow, Airflow, Kubeflow, Docker, etc.)

Understanding of credit risk modeling, financial products, or consumer lending.

Experience working with APIs, real-time scoring, and event-driven architectures.

Why Join Us?

High Impact: Your models will directly shape how people access loans, improve credit scores, and receive personalized financial recommendations

Innovation-First Culture: From tree-based models to neural networks and LLMs, you’ll have the freedom to prototype with state-of-the-art techniques and put them in action

Cross-Functional Collaboration: Work closely with product, engineering, and business leaders to take ideas from prototype to production.

Mission-Driven: Help democratize financial wellness and unlock opportunities for millions.

Base Salary 

The annual base salary for this position is between $180,000 to $200,000 depending upon experience.

Additionally we provide

Annual Bonus Potential + Equity Compensation package

Vacation/Paid time off

Medical, Dental, Vision – 100% premium paid for employee

Opportunity for career growth and challenge

Beautiful California East Bay offices in Dublin

SavvyMoney’s EEO Statement

SavvyMoney relies on diversity of culture and thought to deliver on our goal of Creative People, Practical solutions serving our client needs, and ensures nondiscrimination in all programs and activities. We continuously seek talented, qualified employees in our operations regardless of race, color, sex/gender, including gender identity and expression, sexual orientation, pregnancy, national origin, religion, disability, age, marital status, citizen status, protected veteran status, or any other protected classification under country or local law. SavvyMoney is proud to be an Equal Employment Opportunity/ Affirmative Action Employer.

We are committed to protecting your data.  To learn more, please review the SavvyMoney Employee Privacy Policy Notice here

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