Remote Data Scientist

Summary

Join our team as a Data Scientist at Candidly to design, develop, and deploy AI-driven features that enhance our financial wellness platform. You will work 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.

Requirements

• 3-5 years of experience in a data science role, with a strong track record of delivering impactful ML solutions
• 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
• 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

Responsibilities

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

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