Position OverviewWe 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.
Key Responsibilities- 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.
Required Qualifications- MS or PhD in Computer Science, Statistics, Mathematics, or related quantitative field
- MS with 6+ years of industry experience or PhD with 3+
- 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
Preferred Qualifications- 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
What We Offer- 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.
Additional Information- 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.
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