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Predictive Analyst Jobs in Massachusetts (NOW HIRING)

Develop predictive and prescriptive analytical models to support product prioritization, customer behavior forecasting, segmentation, roadmap planning, and opportunity scoring. * Analyze results from ...

Develop predictive and prescriptive analytical models to support product prioritization, customer behavior forecasting, segmentation, roadmap planning, and opportunity scoring. * Analyze results from ...

Sr Digital & Marketing Analyst

Milford, MA · On-site

$112K - $138K/yr

Experience with statistical modeling, predictive analytics, machine learning techniques, customer segmentation, clustering, and classification models. * Experience integrating digital analytics with ...

Sr Digital & Marketing Analyst

Milford, MA · On-site

$112K - $138K/yr

Experience with statistical modeling, predictive analytics, machine learning techniques, customer segmentation, clustering, and classification models. * Experience integrating digital analytics with ...

Advanced SQL skills required; experience with statistical predictive analytics tools like R and Python preferred. * Natural analytical curiosity is essential. * Must demonstrate attention to detail ...

Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in ...

Who holds 3-5+ years of experience Customer Analytics delivery Who holds 3+ years of experience in CRM Modeling, Reporting, Analytics who is experienced in predictive analytics tools Qualifications ...

Showing results 21-40

Predictive Analyst information

What are the key skills and qualifications needed to thrive as a predictive analyst?

To thrive as a Predictive Analyst, you need a strong background in statistics, data analysis, and a relevant degree such as mathematics, computer science, or economics. Proficiency with data analytics tools like Python, R, SQL, and machine learning platforms, as well as familiarity with data visualization software, is typically required. Strong problem-solving abilities, critical thinking, and effective communication skills help you translate complex data findings into actionable business insights. These skills and qualifications are essential for delivering accurate forecasts that drive strategic decision-making and business growth.

How does a predictive analyst typically collaborate with other teams within an organization?

Predictive Analysts often work closely with cross-functional teams such as marketing, product management, and IT. They translate complex data findings into actionable insights for business decision-makers, requiring strong communication skills and the ability to present data visually. Collaboration may involve regular meetings to define project goals, share progress, and refine predictive models based on team feedback. This interdepartmental cooperation ensures that analytics align with overall business strategies and deliver measurable value.

What is a predictive analyst?

A Predictive Analyst is a professional who uses data analysis, statistical techniques, and machine learning models to forecast future outcomes and trends for a business or organization. They collect and interpret large sets of data to identify patterns and make predictions that help guide strategic decisions. Predictive Analysts often work with various software tools and collaborate with other departments to improve business performance and anticipate future challenges or opportunities.

What is the difference between Predictive Analyst vs Data Analyst?

AspectPredictive AnalystData Analyst
Required CredentialsBachelor's in Statistics, Data Science, or related field; often certifications in predictive modelingBachelor's in Data Analysis, Statistics, or related field; certifications in data visualization or analysis tools
Work EnvironmentAnalytical teams, data science departments, often in tech, finance, or healthcareBusiness units, reporting teams, across various industries
Employer & Industry UsageUsed in industries requiring forecasting and predictive modeling, like finance, marketing, healthcareUsed broadly for data reporting, visualization, and descriptive analysis across industries

Predictive Analysts focus on building models to forecast future trends using statistical and machine learning techniques, while Data Analysts primarily interpret existing data to generate reports and insights. Both roles require strong analytical skills, but Predictive Analysts typically have more specialized training in predictive modeling and data science tools.

What are popular job titles related to Predictive Analyst jobs in Massachusetts? For Predictive Analyst jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Predictive Analyst jobs in Massachusetts look for? The top searched job categories for Predictive Analyst jobs in Massachusetts are:
Infographic showing various Predictive Analyst job openings in Massachusetts as of August 2026, with employment types broken down into 85% Full Time, 7% Part Time, 1% Temporary, and 7% Contract. Highlights an 81% Physical, 7% Hybrid, and 12% Remote job distribution.

Senior Product Data Analyst

Azenta

Burlington, MA

Full-time

Re-posted 10 days ago


Azenta Life Sciences rating

7.5

Company rating: 7.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

65th of 120 rated laboratories


Job description

Azenta Inc.At Azenta, new ideas, new technologies and new ways of thinking are driving our future. Our customer focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships.
All we accomplish is grounded in our core values of Customer Focus, Achievement, Accountability, Teamwork, Employee Value and IntegrityJob TitleSenior Product Data AnalystJob Description

We are hiring a Senior AI Product Data Analyst to drive actionable insights, shape product strategy, and accelerate the adoption of AI-enabled decision making across digital products and customer experiences.

As a core member of the Product organization, this role will partner with Product Management, UX, Engineering, Data, and Business stakeholders to define success metrics, measure user behavior, evaluate AI-enabled features, and uncover opportunities where analytics, machine learning, automation, and generative AI can deliver measurable business value. This individual will combine strong analytical expertise with modern AI capabilities to transform data into insights, predictions, recommendations, and intelligent product improvements.

This role is onsite 4 days/week in Burlington, MA

Key Responsibilities

  • Define, influence, and maintain core product KPIs that inform feature adoption, user engagement, retention, customer experience, and business value.
  • Conduct deep-dive analyses on product performance, user behavior, funnel conversion, feature usage, and digital journey effectiveness.
  • Identify opportunities to apply Artificial Intelligence (AI), Machine Learning (ML), automation, and Generative AI to improve digital products, customer experiences, insight generation, and operational efficiency.
  • Design and measure AI-specific KPIs including adoption, utilization, accuracy, relevance, usefulness, productivity gains, customer satisfaction, user trust, and business impact.
  • Develop predictive and prescriptive analytical models to support product prioritization, customer behavior forecasting, segmentation, roadmap planning, and opportunity scoring.
  • Analyze results from A/B and multivariate tests to evaluate product experiments, AI-enabled features, recommendation logic, and performance impact.
  • Build and maintain self-serve dashboards in Power BI or Tableau to support product transparency, executive visibility, and data-driven decision-making.
  • Use AI-assisted analytics tools and Large Language Models (LLMs) to accelerate data exploration, root-cause analysis, summarization, narrative development, and decision support.
  • Partner with Engineering and Data teams to validate data pipelines, telemetry, model outputs, feature performance, and AI-driven recommendations.
  • Communicate complex findings through visual storytelling, concise executive summaries, and product recommendations that translate data into action.
  • Support data definition, documentation, metadata alignment, and analytics governance across Product, UX, Engineering, and Business stakeholders.
  • Promote responsible AI practices, including explainability, human oversight, data privacy, security, bias awareness, governance, and validation of AI-generated outputs.
  • Build reusable analytics assets, prompts, dashboards, measurement frameworks, and documentation that help teams use AI responsibly and consistently.

Required Qualifications

  • 5+ years in data, product, business analytics, or digital analytics roles with measurable impact on digital product performance.
  • Proficiency in SQL and Python for querying, analysis, automation, statistical analysis, and scalable analytical workflows.
  • Strong skills in Power BI, Tableau, or similar tools for dashboard creation, reporting, measurement frameworks, and executive-ready insights.
  • Experience conducting behavioral, product, funnel, retention, cohort, journey, and experimentation analysis using large-scale data.
  • Experience applying machine learning, predictive analytics, advanced statistical methods, or AI-assisted analytics to solve business or product challenges.
  • Working knowledge of machine learning concepts, model evaluation techniques, predictive modeling approaches, and responsible use of AI-generated insights.
  • Ability to critically evaluate model outputs and AI-generated recommendations, validate results against source data, and clearly communicate assumptions, limitations, and business implications.
  • Excellent communication and data storytelling skills, with experience presenting to product, business, technical, and executive stakeholders.
  • Experience defining metrics, synthesizing complex data sources, and delivering insight in agile, cross-functional teams.
  • Familiarity with data governance, data privacy, security controls, metadata management, and responsible AI principles.

Preferred Qualifications

  • Experience designing analytics solutions for AI-enabled products, digital platforms, intelligent automation, or customer-facing digital experiences.
  • Experience using Generative AI or LLM-based tools such as Microsoft Copilot, Azure OpenAI, ChatGPT Enterprise, Claude, or equivalent technologies to support analytics, insight generation, automation, or product discovery.
  • Familiarity with prompt engineering, AI-assisted workflow design, natural-language analytics, or automated insight-generation approaches.
  • Exposure to machine learning use cases such as forecasting, recommendation engines, anomaly detection, churn/retention modeling, personalization, clustering, propensity scoring, or prioritization models.
  • Experience measuring and optimizing AI feature adoption, recommendation quality, conversational AI performance, copilots, personalization capabilities, or model usefulness.
  • Experience with Azure AI services, Azure OpenAI, Databricks, Snowflake, Microsoft Fabric, or other cloud-scale analytics environments.
  • Knowledge of model monitoring, model lifecycle management, experimentation frameworks, explainability, bias mitigation, and human-in-the-loop validation.
  • Experience in enterprise SaaS, B2B, digital commerce, life sciences, healthcare technology, or regulated environments.
  • Familiarity with experimentation platforms such as Adobe Target, Optimizely, or similar tools.
  • Exposure to compliance frameworks such as GDPR, 21 CFR Part 11, or relevant data governance and privacy standards.

EOE M/F/Disabled/VET

    If any applicant is unable to complete an application or respond to a job opening because of a disability, please email at Recruiting@azenta.com for assistance.

    Azenta is an Equal Opportunity Employer. This company considers candidates regardless of race, color, age, religion, gender, sexual orientation, gender identity, national origin, disability or veteran status.

    United States Base Compensation: $107,000.00 - $134,000.00

    The posted pay range for this position is an estimate based on current market data and internal pay structure. Final compensation may vary above or below this range depending on factors such as experience, education (including licensure and certifications), qualifications, performance, and geographic location, among other relevant business or organizational needs.


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