Data Scientist

Remote - USA

Candidly

Explore Candidly's innovative financial wellness benefits for employees. We help your team repay student debt, plan for college, and save for the future.

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Company Description

Candidly was founded in 2016 to flip the script on what it means to plan, borrow, repay, and save for college. Today, we’re the category leader with the market’s most comprehensive AI-driven student debt and savings optimization platform. We partner with hundreds of top employers, financial institutions, and retirement record keepers, positioning Candidly to serve more than 35 million Americans. 

We’re already achieving incredible results — to date, we’ve helped our users get on track to eliminate more than $1.8B in student debt and pay off their loans 175,000 years quicker — and we’re seeking movers, shakers, innovators, and problem solvers to help take our mission even further. 

Candidly is a high-growth, Series B startup, funded by leading investors including Altos Ventures, Aflac, Salesforce Ventures, UBS, Equal Opportunity Ventures, Impact Engine, Rethink Impact, Unum, and Cercano Management. Our fully remote, international team of 70 (and counting) includes alumni from Google, UBS, Twitter, Plaid, Prudential, LendingTree, Morgan Stanley, Deutsche Bank, and more.

Role Overview

As a Data Scientist at Candidly, you will work on designing, developing, and deploying AI-driven features that enhance our financial wellness platform. You will partner closely with the product and engineering teams to create solutions that leverage machine learning and data analytics to optimize the user experience, improve engagement, and enhance operational efficiencies. You will contribute to projects ranging from predictive modeling to data visualization and beyond, leveraging both structured and unstructured data to deliver innovative financial wellness tools.

Key Responsibilities

  • ML Product Development: Design and build machine learning models to support new product features, including AI-powered guidance and personalized product experiences.
  • Research & Innovation: Stay on the cutting edge of AI/ML advancements, including LLMs, and evaluate new techniques for application within the Candidly platform.
  • Data Analysis & Insights: Conduct exploratory data analysis to uncover trends, patterns, and opportunities for product improvements and new features.
  • Predictive Modeling: Develop and deploy predictive models to anticipate user needs, preferences, and behaviors, enabling proactive and personalized financial guidance.
  • Data Strategy & Engineering: Collaborate with data engineering teams to define data needs, build ETL pipelines, and deploy machine learning models in production environments.
  • Model Evaluation & Tuning: Conduct rigorous testing, optimization, and continuous evaluation of deployed models to ensure they deliver impactful and reliable results.
  • Stakeholder Collaboration: Work closely with stakeholders across product, design, engineering, and leadership to translate complex AI concepts into actionable strategies and features.
  • Data Storytelling: Present findings and insights in a compelling way to both technical and non-technical audiences, contributing to strategic decision-making. 

Requirements

  • Experience: 3-5 years of experience in a data science role, with a strong track record of delivering impactful ML solutions.
  • Technical Skills:
    • A love of experimenting and working with new tools and technologies, including LLMs.
    • Strong programming skills in Python and proficiency with libraries such as TensorFlow, PyTorch, Scikit-Learn, Pandas, and NumPy.
    • Expertise in machine learning techniques such as supervised and unsupervised learning, deep learning, and ensemble methods.
    • Proficiency in designing and deploying ML pipelines for data preprocessing, feature engineering, model training, and evaluation.
    • Expertise in designing and deploying machine learning models for production.
    • Familiarity with cloud platforms (AWS) and tools for model deployment and orchestration.
    • Strong skills in SQL and data visualization libraries.
  • Soft Skills:
    • Strong communication skills and ability to explain complex concepts to non-technical stakeholders.
    • High adaptability and comfort working in a dynamic, fast-paced startup environment.
    • Proactive, with a passion for building impactful solutions that address real-world challenges.

Preferred Qualifications

  • Experience in FinTech, financial services, or consumer lending domains.
  • Proven track record of developing AI/ML solutions focused on user engagement or personalized recommendations.
  • Hands-on experience with advanced ML techniques such as reinforcement learning, graph neural networks, or Bayesian methods.
  • Familiarity with LLMs and their applications in AI-driven products.

Background and EEOC

Candidly offers for employment are conditioned upon satisfactory completion of our employment screening process (including, but not limited to, a review of past employment and education records, background investigation, and/or credit check & fingerprints).

Candidly strives to foster an environment where every employee can succeed. As an Equal Opportunity Employer we do not discriminate on the basis of race, religion, color, sex, sexual orientation, gender identity, gender expression, national origin, age, non-disqualifying physical or mental disability, veteran status, or any other basis covered by applicable law. All employment is decided on the basis of qualifications, merit, and business need.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Data Science Jobs

Tags: AWS Bayesian Data analysis Data Analytics Data strategy Data visualization Deep Learning EDA Engineering ETL Feature engineering FinTech LLMs Machine Learning ML models Model deployment Model training NumPy Pandas Pipelines Predictive modeling Python PyTorch Reinforcement Learning Research Salesforce Scikit-learn SQL TensorFlow Testing Unstructured data Unsupervised Learning

Perks/benefits: Career development Startup environment

Regions: Remote/Anywhere North America
Country: United States

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