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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 ...

GMO

Data Platform Analyst

Boston, MA · Hybrid

$80/hr

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 ...

GMO

Data Platform Analyst

Boston, MA · On-site

$80/hr

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 ...

Massgeneralbrigham

Data Analyst/Programmer

Boston, MA · Hybrid

$53K - $75K/yr

Proficiency in R / Bioconductor and/or Python (both preferred) Experience in the linux environment and command line Excellent communication (oral and written) and documentation skills, and ability to ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus * Experience working with and analyzing ...

Azenta

Senior Product Data Analyst

Burlington, MA · On-site

Proficiency in SQL and Python for querying, analysis, automation, statistical analysis, and ... Excellent communication and data storytelling skills, with experience presenting to product ...

Azenta

Senior Product Data Analyst

Burlington, MA · On-site

Proficiency in SQL and Python for querying, analysis, automation, statistical analysis, and ... Excellent communication and data storytelling skills, with experience presenting to product ...

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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.

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.

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.

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.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.
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For Python Data Analyst jobs in Massachusetts, the most frequently searched job titles are:

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Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Platform Analyst

GMO

Boston, MA • Hybrid

$155K - $170K/yr

Full-time

Re-posted 12 days ago

Job description

Company Profile
 
Founded in 1977, GMO is a global investment manager committed to delivering superior long-term investment performance and advice to our clients. We offer investment strategies and solutions where we believe we are positioned to add the greatest value for our investors. These include multi-asset class, equity, fixed income and alternative offerings.
 
We manage approximately $80bn for a client base that includes many of the world’s most sophisticated institutions, financial intermediaries, and private clients. Industry-wide, we are well known for our focus on valuation-based investing, willingness to take bold positions when conditions warrant, and candid and academically rigorous thought leadership. Jeremy Grantham, GMO’s Co-Founder and Long-Term Investment Strategist, is renowned as an expert in identifying speculative investment bubbles and also as a leading climate investor and advocate.
 
GMO is privately owned and employs over 430 people worldwide. We are headquartered in Boston, with additional offices in Europe, Asia and Australia. Our company-wide culture emphasizes commitment to clients, intellectual curiosity, and open debate. We celebrate and respect our differences, while embracing and valuing what each of us brings to work, as we know that diverse teams in an inclusive, caring environment achieve higher engagement and better client results.
 
Please follow the prompts included in this job posting to apply. The application window for this role is anticipated to remain open until the job is filled, or as otherwise determined by GMO.
 

Position Overview

We are seeking an experienced Data Platform Analyst to join GMO’s Data Engineering and Operations team within the Technology group. This role offers an opportunity for a seasoned Analyst to leverage their financial reference data and enterprise data platforms experience to evolve GMO’s security master data and portfolio data platforms. Partnering with GMO’s Operations and Investment teams, a successful candidate will translate operational insight into scalable workflow, control, automation, and data quality improvements. They will bring deep experience in Neoxam’s DataHub application and a proven track record leading or supporting security master conversions and data platform migrations.

The position will be based in Boston where GMO is currently operating in a hybrid work model, with the current expectation that this person will be in the office for a minimum of 2 days per week and the balance of the week working either in the office or remotely.

Responsibilities
  • Develop an expert understanding of GMO’s reference data flow within internal databases and vendor applications: BlackRock Aladdin, NeoXam DataHub, and Eagle PACE
  • Act as the NeoXam DataHub application subject matter expert: validate portfolio master and other reference data, resolve production issues, and ensure scalable integration with downstream systems
  • Through hands-on operational execution, identify recurring issues, process gaps, and data quality risks; translate findings into business requirements and recommendations for workflow, control, automation, and data quality improvements
  • 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 transformation activities for portfolio, security master, and reference data across enterprise platforms, including data model review, conversion analysis, controls, and cross-functional stakeholder alignment
  • Think critically to help automate or improve processes and procedures (e.g. control reports, daily checklist)
  • Create business requirements for the onboarding of new datasets and collaborate with software developers to test and implement data processing/storage
  • Explore artificial intelligence tools to enhance existing reference data operations, data quality controls, and production monitoring processes
  • Participate in the team’s evolution from manually maintaining data to maintaining and monitoring data definitions, quality service-level expectations, exception thresholds, and downstream consumption patterns
  • Partner with data engineering and business stakeholders to modernize static data quality rules, such as null checks, format checks, and cross-field validations, by introducing contextual quality validation that can learn from historical data, market behavior, and cross-dataset relationships
Required Skills
  • 10+ years of relevant investment industry experience, working with reference or research data
  • Strong expertise in portfolio/security master data structures and lifecycle events
  • Hands-on experience with NeoXam DataHub (mandatory)
  • Strong data analysis skills using python and SQL; ability to work with large datasets
  • Proven experience supporting or leading security master platform conversions/migrations
  • Working knowledge of Artificial Intelligence tools and a demonstrated interest in applying them to evolving business needs
  • High energy and positive attitude – candidate should be conscientious, self-directed, and possess a strong work ethic
  • Flexibility to be on call to log in at night as needed on a rotational basis
  • Intellectual curiosity about investment data
  • Attention to detail with a focus on data quality and control
  • Strong analytical, organizational, project management, and written communication skills.
  • Familiarity with BlackRock Aladdin
  • Familiarity with financial market data providers (Bloomberg, LSEG, ICE)
This salary range is estimated for this role and actual pay may be different based on a candidate’s qualifications and/or years of experience. In addition, this position is eligible for a discretionary annual bonus award, which award may be determined by individual, team, department and firm performance, and is subject to the terms of GMO’s compensation plan. This position is also benefits eligible. GMO’s comprehensive benefits program includes medical insurance, dental insurance, life insurance, long-term disability coverage, a 401(k)/profit-sharing retirement plan, open paid time off, leaves of absences, dependent care resources, tuition reimbursement, charitable gifts matching, flexible spending accounts, and commuter benefits.
GMO is committed to the recruitment, employment, and promotion of all candidates equally, regardless of an individual's gender, race, color, national origin, ancestry, age, religion, pregnancy, marital status, sexual orientation, gender identity or expression, military or veteran status, genetic information, physical or mental disability (except where such disability is a bona fide occupational disqualification) or any other classification protected under federal, state or local law.
 
GMO will not offer visa sponsorship for this opportunity.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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About GMO

Sourced by ZipRecruiter

Industry

Finance and insurance

Company size

501 - 1,000 Employees

Headquarters location

Boston, MA, US

Year founded

1977

Social media

Twitter

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