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Python Data Analyst Jobs in Massachusetts (NOW HIRING)

GMO

Data Platform Analyst

Boston, MA · Hybrid

$155K - $170K/yr

Analyze data in multiple databases and use a combination of vendor toolsets, Python, SQL, and Excel to develop recommendations to improve data quality * Support the design, governance, and ...

New

Citizens

Experiential Marketing Sr Data Analyst

Westwood, MA · On-site +1

$104K - $138K/yr

Data Analysis & Insights: Conduct complex analyses and create reports to identify trends, uncover ... Advanced proficiency with 3+ years experience in SQL, Python, and data visualization tools (Tableau ...

Citizens

Experiential Marketing Sr Data Analyst

Westwood, MA · On-site +1

$104K - $138K/yr

Data Analysis & Insights: Conduct complex analyses and create reports to identify trends, uncover ... Advanced proficiency with 3+ years experience in SQL, Python, and data visualization tools (Tableau ...

PTC

Principal Data Analyst, Marketing Analytics

Boston, MA · On-site

$94K - $116K/yr

The Principal Data Analyst, Marketing Analytics will lead the measurement of customer journey and ... Python, R, or other statistical programming languages • Hands-on experience with cloud data ...

Cisco

Data Science Analyst

Maynard, MA · On-site

$149K - $190K/yr

Experience with Python libraries such aspandasfor data manipulation and analysis. * Experience preparing data for dashboards or business intelligence tools such asPower BIorTableau. Why Cisco? At ...

Staples, Inc.

Sr Data Solutions Analyst

Framingham, MA · On-site

$88K - $111K/yr

Data Engineering & Data Management * Design, develop, and maintain scalable data pipelines to ... Develop and support tools, scripts, or analytic solutions (e.g., SQL/Python-based automation)

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Massachusetts

Python Data Analyst information

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

What is the difference between Python Data Analyst vs Data Scientist?

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Will AI replace a data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding business context, and communicating findings, which require human judgment. Data analysts who develop skills in programming, data visualization, and machine learning can adapt to new technologies and continue to add value in data-driven decision-making.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as SQL, Python, and data visualization, along with practical experience and certifications. Employers value diverse backgrounds and experience, making it possible to start a data analyst career at any age.

What are the key skills and qualifications needed to thrive as a Python Data Analyst, and why are they important?

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python a high paying job?

Python Data Analysts are generally well-compensated due to their technical skills in programming, data manipulation, and analysis. Salaries vary based on experience, location, and industry, but proficiency in Python often leads to higher earning potential compared to many other entry-level roles in data analysis. Certifications and knowledge of related tools like SQL or machine learning can further increase salary prospects.

Is Python useful for data analysts?

Python is highly useful for data analysts because it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.
More about Python Data Analyst jobs
What are the most commonly searched types of Python Data Analyst jobs in Massachusetts? The most popular types of Python Data Analyst jobs in Massachusetts are:
What are popular job titles related to Python Data Analyst jobs in Massachusetts? For Python Data Analyst jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Python Data Analyst jobs in Massachusetts look for? The top searched job categories for Python Data Analyst jobs in Massachusetts are:
What cities in Massachusetts are hiring for Python Data Analyst jobs? Cities in Massachusetts with the most Python Data Analyst job openings:
Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Massachusetts as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 80% Full Time, 12% Part Time, 2% Temporary, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.
Staff AI Data Analytics Engineer

Staff AI Data Analytics Engineer

Symbotic

Wilmington, MA • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Symbotic is an automation technology leader reimagining the supply chain with its AI-powered robotic and software platform. They are seeking a Staff AI Data Analytics Engineer to design and build an intelligent analytics ecosystem that aggregates operations data and leverages agentic AI for insights and recommendations.
Responsibilities:
• Aggregate and unify data across disparate systems.
• Design scalable data models and pipelines to enable reliable and real-time analytics.
• Leverage agentic AI tools to dynamically generate reports and dashboards.
• Build solutions that provide both real-time visibility and historical trend analysis across key business initiatives.
• Implement AI-driven workflows to automate data analysis, reporting, insight generation, and risk mitigation strategies.
• Develop intuitive, executive-ready dashboards that highlight key performance indicators and insights.
• Collaborate with cross-functional analytics and business partners to align on priorities and ensure insights translate into measurable outcomes.
• Ensure reporting is actionable and aligned to business priorities.
• Analyze data to identify risks, inefficiencies, and performance gaps
• Provide clear, data-driven recommendations to mitigate risks and improve outcomes.
• Establish and enforce enterprise-wide data governance and standards, including clear ownership of core metrics across systems, metric definitions, calculation methodologies, source-of-truth alignment across systems.
• Lead data governance and data quality efforts, including identifying and remediating inconsistencies across data sources and pipelines, and ensuring accuracy, consistency, and trust in analytics outputs.
Qualifications:
Required:
• Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
• Minimum of 8 years of experience in Data Engineering, Analytics Engineering, or Data Science with a strong foundation in statistical analysis and data modeling.
• Experience building agentic AI frameworks for analytics automation.
• Strong proficiency in SQL and Python (data manipulation, analysis, automation).
• Expertise in data visualization tools (e.g., Tableau, Power BI, Looker).
• Experience working with large, multi-source datasets and building scalable data models.
• Demonstrated hands-on coding capability, with experience designing, building, and maintaining production-grade data pipelines and analytics systems.
• Experience defining and implementing data governance frameworks, including metric standardization, data ownership models, and source-of-truth alignment.
• Strong business acumen with the ability to translate data into actionable insights.
• Comfortable operating in a fast-paced, high-growth environment where speed, ownership, and adaptability are critical.
Company:
Symbotic is a provider of integrated supply network automation solutions for warehouses and distribution centers. Founded in 2005, the company is headquartered in Wilmington, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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