Senior Data Scientist/Machine Learning Scientist at Datalign Advisory

Job description

Datalign is an AI-native organic growth partner for wealth management firms. Since launching from Cambridge's innovation hub in 2022 with Link Ventures as our lead investor, we've helped over 100,000 Americans with more than $80 billion in potential client assets connect with 13,000 trusted advisors. Our platform uses AI to connect advisors with high-intent consumers and unlock new opportunities, and our modular suite of organic growth solutions is purpose-built for Registered Investment Advisors (RIAs). Position Overview We are seeking a Senior 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 or personalization 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. • Salary Range: 150-170K

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Position Overview
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.
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
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.

Nice-to-haves

Preferred Qualifications • Experience with graph representations/graph neural networks, real-time ML systems and/or matching or personalization algorithms.

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