Senior or Principal Data Scientist​/Machine Learning Scientist

Position Overview

We are seeking a Senior or Principal Data Scientist/Machine Learning Scientist to lead product-focused artificial intelligence initiatives and facilitate strategic decision-making through advanced analytics and machine learning. This role requires a proven track record of building and scaling data science products that directly impact user experience and business outcomes.

As Data Scientist/Machine Learning Scientist, you will shape the future of how consumers connect with vetted financial advisory firms through our proprietary three-sided marketplace, leveraging data and AI‑powered analytics to create meaningful one‑to‑one matches and improved financial outcomes.

Please note:

We are only accepting applications from candidates in the Greater Boston area, as this is a hybrid role with 4 days a week in office.

• Conduct exploratory data analysis to uncover relationships, patterns and key features in data for both business decision making and model development.
• Develop and deploy machine learning models for production using robust CI/CD practices in collaboration with software engineers.
• Identify success metrics and build evaluation frameworks for both model and product performance considering both technical and business requirements.
• Innovate with the latest generative AI and graph-based machine learning advancements to improve existing processes and develop new products.
• Contribute to architectural and code reviews to maintain and evolve the health of our technical stack.
• Collaborate with product management, engineering, and business teams to rapidly identify and test high‑impact solutions for business needs.
• Influence strategic decisions across multiple business areas by clearly communicating complex data in a way that is understandable and actionable for technical and non‑technical stakeholders.

• MS or PhD in Computer Science, Statistics, Mathematics, or related quantitative field.
• MS with 6+ years of industry experience or PhD with 3+ years of experience.
• Entrepreneurial mindset with willingness to experiment, iterate quickly and move from hypothesis to implementation to develop critical business solutions.
• Expert‑level proficiency in Python, SQL, and distributed computing frameworks.
• Deep understanding of machine learning algorithms, experiment design and statistical modeling and evaluation.
• Strong background in product analytics, classifiers, recommendation systems, and personalization algorithms.
• Experience putting machine learning solutions in production with modern ML platforms (e.g. AWS/GCP/Azure ML, MLflow, Kubeflow).
• Familiarity with A/B testing, product metrics and user behavior analytics.

• Experience with graph representations/graph neural networks, real‑time ML systems and/or matching algorithms.
• Proficiency in big data technologies (e.g. Spark, Dask, Kafka, Airflow) and cloud architectures.
• Background in fintech, wealth management, or financial advisory services with an understanding of the regulatory requirements in financial services.
• Track record of publications in top‑tier conferences or journals.
• Understanding of marketplace dynamics and multi‑sided platform optimization.
• Experience with data monetization and building data products.

• A dynamic, team‑centric and supportive environment in the heart of Kendall Square where your work has a direct impact on enhancing financial advisory services.
• Competitive salary with performance‑based bonuses.
• Comprehensive benefits package including health, dental, and vision insurance, and retirement savings plan.
• Commuting is on us and we will pay for your monthly parking, T Pass or commuter rail pass. We also offer a corporate Bluebike membership.
• Opportunities for professional growth and development within a rapidly growing company.
• Weekly lunches catered to the office.
• Fully stocked kitchen covering all of coffee, tea and snack needs.

• We are only accepting applications from candidates in the Greater Boston area, as this is a hybrid role with 4 days a week in office.
• The level of this position can be adjusted based on the candidate's experience.