> Markdown version of [/jobs/ext/3608169-data-scientist-machine-learning-scientist](https://www.wearedevelopers.com/jobs/ext/3608169-data-scientist-machine-learning-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist/Machine Learning Scientist

- **Company:** Datalign Inc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $150,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Big Data, Software Code Optimization, Code Review, Continuous Integration, Distributed Computing Environment, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, SQL Databases, Cloud Platform System, Graph Neural Networks, Apache Spark, Kubernetes, Information Technology, Dask, Apache Kafka, Machine Learning Operations
- **Published:** October 7, 2026
- **Apply:** https://www.builtincolorado.com/job/senior-data-scientist-machine-learning-scientist/11528681?handler=ApplyRedirect

## About the Role

The summary above was generated by AI, * 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, * 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

## Description

Lead product-focused data science and machine learning initiatives, including exploratory analysis, production model development, evaluation frameworks, generative AI, graph-based machine learning, recommendation systems, and personalization. Collaborate with engineering, product, and business teams to deliver high-impact solutions, influence strategy, and communicate insights to technical and non-technical stakeholders. The hybrid role requires four days per week in the Greater Boston area., 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., * 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.