Lead Data Scientist

Aperture Cloud was founded in 2016 on the belief that objective, personalized financial advice is essential to living well. Our mission is to empower people to live more enriched lives by delivering a new standard of advice. By removing asset minimums, we provide holistic planning that goes far beyond investments to address every way money impacts life. To achieve this, we leverage a "human-plus-tech" approach, combining the expertise of CFP® professionals with cutting-edge AI and automation. This model allows Aperture Cloud to integrate advice into our members’ entire financial picture—all for an affordable, flat membership fee. Our commitment to innovation and member success has earned national recognition, including being ranked the #1 Best Financial Advisory Firm 2025 by USA TODAY and named to Newsweek’s list of America’s Top Financial Advisory Firms 2025. With an A+ BBB Rating and a Trustpilot “Excellent” score (as of Sept. 16, 2025)*, we are proud to be redefining the industry for our members and our team alike. Why Join the Aperture Cloud Data Science Team? Diverse Problems: We partner with every team at Aperture Cloud on cross-departmental initiatives that directly improve the member experience and level up our workflows. Optimization, classical ML, NLP, and LLMs are all on the table. We pick the right tool for the job, not the most familiar one. End-to-End Ownership: You own the data science workflow from problem framing through deployment: scoping, dataset construction, modeling, and delivery. You'll partner closely with engineering and product teams to bring your work into production. Visible impact: Your work shapes decisions across the company. On a team this size, there's a short line between what you build and the value you deliver. Responsibilities: As a Staff Data Scientist with a focus on both reporting and predictive modeling, your day-to-day responsibilities will include a mix of tasks related to data analysis, visualization, and predictive model development. Your core duties will consist of: Exposing Insights : As a Data Scientist, your goal is not to just display data, but turn it into information. You will produce analysis reports and diagnostic models to try and discover hidden relationships and patterns between our data and metrics of interest. Evaluate & Produce Qualit y: Good code is reviewed code. You will be involved in ensuring your and your teammates’ code is free from errors, bias, and is easy to understand. Data Engineering: We are a newer team at a growing company, and you’ll need to do a lot of your own data engineering. Gather, clean, and preprocess data from various sources, ensuring accuracy and consistency. Perform feature engineering to generate new variables or transform existing ones to improve the quality and usefulness of the dataset. Tie all these tasks together in a pipeline and deploy on cloud based infrastructure. Predictive Modeling : Develop, validate, and deploy predictive models using machine learning algorithms and statistical techniques, such as regression, classification, clustering, time series forecasting, and optimization. Generative Modeling: Use a combination of open source and paid technologies to produce abstractions & novel features for other applications. Continuous Improvement: Data Science is a quickly moving field and you’ll need to keep up to date. You will need to keep abreast of the latest developments in data science, machine learning, and reporting technologies, while incorporating them into your work when appropriate. Participate in knowledge-sharing sessions to contribute to the growth and development of others. Requirements 7+ years of experience in a data science or machine learning role Experience with at least one dashboarding tool, such as: Tableau, Power BI, Looker, Google Data Studio, Streamlit, Dash, etc… Proficiency with Python Proficiency with SQL Knowledge of machine learning algorithms and statistical techniques for predictive modeling, such as: Regression, Classification, Clustering, Time Series Analysis, and Optimization Proficiency with end-to-end pipelines Expert knowledge in model evaluation metrics Experience pulling data from various third party systems and APIs Proficiency with version control Proven ability to work both independently and as part of a team Proficiency with visualization in python Familiar with best practices in secure data handling and customer data privacy Proven record of converting business problems to data science solutions Preferred Experience: Prior experience in the financial planning industry Prior experience in the consumer technology industry Prior experience using containers to produce repeatable and shareable code Prior experience with Natural Language Processing Prior experience with cloud deployment Prior experience with Neural Networks and/or LLMs Prior experience with business optimization Benefits Competitive Compensation : $180,000 - $220,000 base salary + bonus Ownership : Equity in a rapidly growing company on the