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Full Time Data Scientist Machine Learning Jobs in Boston, MA

They are seeking a Senior Data Scientist to develop AI and machine learning solutions that will enhance product offerings and optimize business strategies. Responsibilities : • Engage with business ...

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Experience adapting novel machine learning approaches (e.g., from academic literature) to new data ... data * Experience in intelligence or military-related mission areas Pay Information Full-Time ...

Senior Data Scientist Serve as a senior member of the team focused on data science, machine learning, stochastic generation models, data visualization, algorithm development, natural language ...

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Full Time Data Scientist Machine Learning information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do full time data scientist machine learning jobs pay per year?

As of Jul 27, 2026, the average yearly pay for full time data scientist machine learning in Boston, MA is $133,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,800.00 per year, depending on experience, location, and employer.

What are some common challenges faced by full-time Data Scientists specializing in Machine Learning, and how can they be addressed?

Full-time Data Scientists in Machine Learning often encounter challenges such as dealing with messy or incomplete data, tuning complex models for optimal performance, and effectively communicating technical insights to non-technical stakeholders. Addressing these challenges usually involves collaborating closely with data engineers to improve data quality, staying updated with the latest ML techniques, and developing strong communication skills to translate findings into actionable business strategies. Additionally, regular code reviews and participation in cross-functional meetings help ensure alignment and foster a supportive team environment.

What does a Full Time Data Scientist specializing in Machine Learning do?

A Full Time Data Scientist specializing in Machine Learning is responsible for analyzing large datasets to discover patterns and insights, and for building, testing, and deploying machine learning models to solve business problems. They use statistical techniques, programming skills, and domain knowledge to turn raw data into actionable information. Their day-to-day tasks often include data cleaning, feature engineering, model selection, and performance evaluation. They also collaborate with other teams to integrate machine learning solutions into products or decision-making processes. This role typically requires proficiency in languages like Python or R, and familiarity with tools such as TensorFlow, scikit-learn, or PyTorch.

What are the key skills and qualifications needed to thrive as a Full Time Data Scientist Machine Learning, and why are they important?

To thrive as a Full Time Data Scientist Machine Learning, you need strong analytical skills, expertise in statistics, machine learning techniques, and a relevant degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, experience with machine learning libraries like TensorFlow or scikit-learn, and familiarity with data visualization and big data platforms are typically required. Critical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating with stakeholders and translating data insights into business value. These skills are crucial for developing robust models, interpreting complex data, and driving impactful, data-driven decisions within organizations.

What is the difference between Full Time Data Scientist Machine Learning vs Data Analyst?

AspectFull Time Data Scientist Machine LearningData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related; proficiency in data visualization and SQL
Work EnvironmentDeveloping ML models, programming in Python/R, deploying algorithmsData cleaning, reporting, creating dashboards, analyzing datasets
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Full Time Data Scientist Machine Learning roles focus on building and deploying machine learning models, requiring advanced programming and statistical skills. Data Analysts primarily interpret data, generate reports, and support decision-making with less emphasis on ML techniques. Both roles are vital but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Boston, MA? The most popular types of Data Scientist Machine Learning jobs in Boston, MA are:

Senior or Principal Data Scientist/Machine Learning Scientist

Datalign Advisory, Inc.

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 15 days ago


Job description

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.
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.