Senior/Staff Data Scientist (Consumer Apps, Klover)

Klover; Chicago (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

Attain in Chicago, IL, is seeking a Senior/Staff Data Scientist to build, validate, and deploy predictive models powering consumer decisioning across a suite of fintech apps including earned wage access. You will own end-to-end modeling workflows, from data exploration to retraining, and collaborate with product, analytics, and engineering teams to deliver scalable ML solutions.

Ideal candidates have 5+ years in data science or related roles, strong Python and SQL skills, experience with

Qualifications

• 5+ years direct experience as Data Scientist or similar role.
• Master’s or Ph.D. in a STEM field preferred.
• Strong Python and SQL skills for modeling and data handling.
• Experience deploying ML models in production and MLOps familiarity.
• Experience with cloud platforms, preferably GCP.

Responsibilities

• Build, validate, and deploy predictive models powering decisions across apps.
• Own end-to-end modeling lifecycle from data exploration to retraining.
• Collaborate with analysts, engineers, and product teams to scale ML solutions.
• Develop reusable modeling pipelines and production‑quality code.

Skills

Python

Statistical modeling

Machine learning

Data analysis

SQL skills

Education

Master's degree or PhD in STEM

Tools

GCP

Git

MLflow

Docker

Job description

• Klover’s engineering team powers one of the fastest-growing fintech platforms in the U.S. , supporting over one million active users each month
• Our systems process and move more than $1.5 billion annually, enabling real-time access to financial tools, rewards, and services that help people improve their day-to-day lives
• As part of this team, you’ll help design, build, and scale the systems that underpin Klover’s core products and platform
• You’ll work on high-impact, production-grade systems that prioritize reliability, security, and performance, and that integrate with a broad ecosystem of internal and external services
• The work you do will directly shape how users interact with Klover’s products, access their money, and experience transparent, low-fee financial services
• Klover engineers collaborate closely with colleagues across backend, frontend, data science, and product teams to deliver scalable, high-quality solutions for a rapidly growing user base
• You’ll have the opportunity to work with modern technologies and architectures while helping define and evolve the next generation of inclusive, data-powered financial products—building systems and interfaces that emphasize reliability, privacy, and performance at scale
• Attain is seeking a Senior/Staff Data Scientist to support the growing needs of our suite of B2C financial services
• This role will be highly hands‑on, focused on building, improving, validating, and deploying predictive models that power consumer decisioning and business optimization across our app portfolio
• You will work on advanced machine learning and statistical modeling problems, including cash-flow-based credit decisioning for our earned wage advance product, Klover, as well as consumer behavior modeling, transaction categorization, paycheck detection, fraud scoring, churn prediction, and other high‑impact predictive modeling use cases
• Hands‑on development of ML and statistical models at the core of our EWA product, with a focus on fast, rigorous, and high‑quality execution
• Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business‑critical use cases
• Own the full model development lifecycle, including data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
• Develop reusable modeling pipelines, analytical tools, and production‑quality code to support scalable data science work
• Apply strong statistical and mathematical judgment to model evaluation, calibration, robustness testing, and business impact measurement
• Collaborate with data analysts, engineers, product managers, and business stakeholders to deliver ML models with quality, efficiency, and precision
• Identify new areas where data science, predictive modeling, and optimization can improve product and business outcomes

The ideal candidate combines strong quantitative fundamentals with practical experience building models and analytical systems from scratchAt Attain, we are passionate about finding people to continuously help us grow our organization. We encourage you to apply, even if your experience doesn’t match every detail of the job description5+ years of direct experience working as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role on relevant business problemsStrongly preferred: Master’s, or Ph.D. in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research, or a related quantitative fieldDemonstrated ability to apply critical thinking, causal inference, abstract reasoning, and generalization to complex, ambiguous business and technical problemsStrong expertise developing, validating, deploying, and monitoring machine learning models in productionExperience with AI/ML-assisted development tools and MLOps practices, including experience working with large language models (LLMs) or autonomous agents for code generation and model refinementExperience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling, or other high‑impact applied ML use casesSolid foundation in statistics, probability, mathematics, and machine learning fundamentalsStrong Python coding skills, with the ability to build models, pipelines, and analytical tools from scratchExperience with feature engineering, model evaluation, calibration, monitoring, retraining, and model performance diagnosticsExperience with cloud computing services or platforms; GCP preferredStrong SQL skills and experience working with large, messy, real‑world datasetsFamiliarity with version control, peer code review, and collaborative software development practicesDemonstrated ability to learn new technologies, applications and modeling approaches quicklyWillingness to roll up your sleeves and wear multiple hats across data science, analytics, modeling, and technical execution based on business needsStrong written and verbal communication skills, including the ability to explain technical topics to both technical and non‑technical audiences