Data Scientist

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.