Senior Data Scientist

About Ryewalk

At Ryewalk, we go beyond solving problems - we engineer smart, scalable solutions that drive business success.

● Salesforce Experts – We don’t just implement CRM solutions; we tailor Salesforce to fit your

business, ensuring seamless adoption and maximum impact.

● Cloud Strategists – We design and build cloud architectures in AWS that are robust, scalable, and

ready for the future.

● Tech Trailblazers – When technology challenges stall progress, we step in, streamline, and deliver.

No jargon, no fluff—just outcomes that matter.

● Decision Scientists – We don't just crunch numbers; we turn data into insight and insight into

action—combining analytics, modeling, and decision science to drive smarter business decisions.

If it’s a complex tech challenge, we’re the team that makes it work.

About the Role

We're looking for a Senior Data Scientist to help deliver data science and business analytics solutions for our fintech clients.

This is a hands-on, senior individual-contributor role. You'll spend most of your time deep in the data building models, running analysis, and shipping work that clients act on — while taking full ownership of your workstreams and helping level up more junior members of the team.

The role centers on three things:

● Deep technical craft — you're excellent in the data and hold a high bar for your own work.

● Ownership of delivery — you own your workstreams end-to-end, from ambiguous problems to clear

recommendation, and you deliver reliably.

● Clear communication — you present findings with confidence, work directly with clients in your

areas, and explain complex ideas simply.

If you love being close to the work, take pride in producing rigorous analysis, and enjoy turning messy

problems into clear answers, we'd love to talk.

Key Responsibilities

Hands-On Data Science & Analytics

● Write SQL and Python, build models, run analysis, and create dashboards — this is the core of the

role, day in and day out.

● Design, build, and deploy end-to-end ML models for lending use cases such as credit scoring, risk

assessment, default and early-warning prediction, fraud detection, and customer segmentation.

● Own the full modeling lifecycle: exploratory analysis, feature engineering, model selection,

validation, and performance monitoring.

● Partner with client stakeholders to answer key business questions with data — running ad hoc

deep-dives and recurring analyses that inform product, risk, pricing, and operational decisions.

● Own portfolio and performance analytics — tracking and explaining metrics such as application

and funding conversion, approval rates, delinquency, charge-offs, roll rates, and vintage/cohort

performance.

● Credit Risk Analytics to evaluate changes to credit policy, product, and pricing, and translate the

results into clear, actionable recommendations.

● Design intuitive Tableau dashboards and automated reporting that drive decisions across product,

risk, and operations.

● Follow and help improve best practices for reproducible, scalable, production-ready work.

Delivery & Client Collaboration

● Own the delivery of your workstreams end-to-end — scoping, planning, execution, and on-time

delivery.

● Work directly with client stakeholders on your areas of the project, building trusted relationships

and staying close to their needs.

● Translate ambiguous, open-ended business problems into well-defined analyses with clear

deliverables and timelines.

● Communicate progress clearly, surface risks early, and keep your work on track.

● Present findings and recommendations to both technical and executive audiences with clarity and

confidence.

Mentorship & Quality

● Mentor junior data scientists and analysts, sharing your expertise and helping them grow.

● Bring a quality-first mindset to your own work, and contribute to code, model, and dashboard

reviews to help maintain a high bar across the team.

● Contribute to the team's technical standards and best practices.

● Help unblock teammates and support them on both technical craft and communicating their work.

● Contribute to a culture of curiosity, ownership, and continuous improvement.

What We’re Looking For

Must-Have:

● 4+ years of hands-on experience in data science / business analytics, with a track record of owning

meaningful workstreams and delivering high-quality work.

● A strong sense of ownership — managing your scope, timelines, and stakeholders to deliver

reliably.

● Expert SQL for querying and shaping large-scale datasets.

● Strong Python for data analysis and ML modeling.

● Hands-on expertise with Tableau (or a similar BI tool) for dashboarding and reporting.

● Deep understanding of statistics, hypothesis testing, and data visualization best practices.

● Strong experience with ML libraries/frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).

● Experience taking ML models from prototype to production.

● Excellent communication and presentation skills — able to explain complex technical concepts to

non-technical and executive audiences, and comfortable presenting your work directly to clients.

● A quality-first mindset: strong attention to detail and pride in producing rigorous, reliable work.

● Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.

Nice-to-Have:

● Background in fintech, credit risk, or lending — a strong plus that will help you ramp quickly with the

client.

● Experience mentoring junior data scientists or analysts.

● Experience with cloud data platforms (AWS, GCP, Azure).

● Familiarity with MLOps and model deployment pipelines.

● Experience in a consulting environment.

● Comfort working with US-based / distributed clients across time zones.

● Knowledge of Git, CI/CD, and modern data workflows.

What Success Looks Like

● First 30 days: You've ramped up on the client's data and priorities, built good working relationships

with the team, and taken ownership of your first workstreams.

● Within 3 months: You're consistently shipping high-quality, high-impact work, trusted to run with

complex problems on your own — and you've become a go-to technical contributor the client and

team rely on.

What Makes You a Great Fit

⭐ Problem-Solver Mindset - You enjoy tackling challenges and finding innovative solutions

⭐ Excellent Troubleshooting Abilities - You can quickly diagnose and resolve technical issues under pressure

⭐ Curiosity & Continuous Learning - You stay updated with the latest Data Engineering trends and technologies

⭐ Ownership & Accountability - You take responsibility and drive projects to completion

⭐ Collaboration & Communication - You work well across teams and can explain technical concepts clearly

⭐ Adaptability - You thrive in a dynamic environment and embrace change

⭐ Proactive Approach - You anticipate challenges, take initiative, and suggest improvements before issues arise

Why Ryewalk? 🚀

Impact from Day One

Wear Multiple Hats (If You Want To!)

Work With the Best

Grow at Startup Speed

Hybrid-Friendly & Flexible

Solve Real Problems

Culture That Feels Like Home