1

Python Analytics Jobs in Massachusetts (NOW HIRING)

Preferred At least 4 years of experience in Python programming using CPython. At least 2 years of ... Analytical skills Experience in Energy/Oil&Gas domain Ability to work in team in diverse/ multiple ...

Candidates will work closely with risk analysts and investment teams, but your primary focus will ... Experience with key Python Libraries (pandas, NumPy) required * Experience in frontend development ...

Senior Full Stack Python Developer - Network Automation Type: Contract - 6+ months Location: Boston ... Analytical problem-solving skills with a focus on understanding requirements before implementation

We'relooking for aSenior Python Engineerto join ourever evolvingPazienteamandhelp us unleash the ... You'llbe joining a small team working on expanding a new reporting and analytics product ...

next page

Showing results 1-20

Python Analytics information

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

To thrive as a Python Analytics professional, you need a strong background in statistics, data analysis, and proficiency in Python programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data analytics libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and experience with databases are typically required. Strong problem-solving, communication, and critical thinking skills help in interpreting data and conveying insights to stakeholders. These abilities are crucial for turning complex data into actionable business decisions and driving organizational success.

What is the difference between Python Analytics vs Data Analyst?

AspectPython AnalyticsData Analyst
Required SkillsPython programming, data manipulation, statistical analysisExcel, SQL, basic statistics
CertificationsPython certifications, data analysis coursesNone typically required, but certifications like CAP or Microsoft certifications are common
Work EnvironmentData science teams, analytics departments, tech companiesBusiness units, marketing, finance, consulting firms
ToolsPython libraries (Pandas, NumPy, scikit-learn)Excel, SQL, Tableau, Power BI

Python Analytics involves using Python programming to perform advanced data analysis, modeling, and automation, often requiring coding skills. Data Analysts focus on interpreting data using tools like Excel and SQL, providing reports and insights. While both roles analyze data, Python Analytics typically involves more technical and programming expertise, making it suitable for complex data projects and predictive modeling.

Is Python a high paying job?

Python analytics roles are generally well-paid due to the high demand for data analysis, machine learning, and automation skills. Salaries vary based on experience, location, and industry, but professionals with Python expertise often earn above average wages in the tech and finance sectors.

What are some typical challenges faced by professionals in Python Analytics roles, and how can I prepare for them?

Professionals in Python Analytics roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and communicating insights effectively to non-technical stakeholders. To prepare, it's beneficial to strengthen your skills in data cleaning, visualization libraries (like Matplotlib or Seaborn), and learn best practices for writing efficient, reproducible code. Collaborating closely with data engineers, business analysts, and decision-makers is also a key part of the job, so developing strong communication and teamwork abilities will help you succeed.

What is a Python Analytics professional?

A Python Analytics professional is someone who uses the Python programming language to collect, process, analyze, and interpret data in order to help organizations make data-driven decisions. They often work with large datasets, perform statistical analyses, create data visualizations, and build predictive models. These professionals may work in industries such as finance, healthcare, marketing, or technology, and typically use libraries like Pandas, NumPy, and Matplotlib. Their work helps businesses gain insights, optimize processes, and solve complex problems through data.

What is the salary for Python data analytics?

The salary for Python data analytics roles typically ranges from $70,000 to $120,000 annually, depending on experience, location, and industry. Professionals with strong skills in data manipulation, machine learning, and tools like Pandas or NumPy tend to earn higher salaries.

What does a Python data analyst do?

A Python data analyst uses Python programming to collect, clean, analyze, and visualize data to support business decision-making. They often work with libraries like pandas, NumPy, and matplotlib, and may also perform statistical analysis or build data models. Strong problem-solving skills and knowledge of data management are essential for this role.

Is Python good for data analytics?

Python is widely used in data analytics roles due to its simplicity, extensive libraries like pandas, NumPy, and scikit-learn, and strong community support. It enables analysts to perform data manipulation, visualization, and machine learning tasks efficiently, making it a valuable skill for data analytics jobs.
What job categories do people searching Python Analytics jobs in Massachusetts look for? The top searched job categories for Python Analytics jobs in Massachusetts are:
What cities in Massachusetts are hiring for Python Analytics jobs? Cities in Massachusetts with the most Python Analytics job openings:
Infographic showing various Python Analytics job openings in Massachusetts as of July 2026, with employment types broken down into 1% Internship, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.

Senior Advanced Analytics & Insights Manager

Definitive Healthcare, US

Framingham, MA

$107K - $160K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


Job description

About the Role

We are looking for a Senior Advanced Analytics & Insights Manager with 5+ years of experience to support high-impact analytics work across healthcare and life sciences. This is a hands-on role for someone who can work directly with complex healthcare datasets, apply data science methods, write strong SQL and Python, and translate analytical outputs into clear business recommendations. The ideal candidate will combine technical execution with consulting-style problem solving. They should be comfortable owning analytical workstreams, guiding junior team members, partnering with business stakeholders, and delivering client-ready insights across use cases such as patient journeys, market assessment, targeting, segmentation, forecasting, real-world data analysis, and commercial strategy.

What You'll Do 

  • Lead analytics workstreams from business question definition through data analysis, modeling, interpretation, and final delivery.
  • Work hands-on with large healthcare and life sciences datasets, including claims, provider, patient, market, commercial, or other real-world data.
  • Write efficient SQL to extract, join, transform, validate, and analyze large datasets.
  • Use Python for data wrangling, automation, statistical analysis, modeling, and repeatable analytical workflows.
  • Apply appropriate data science techniques such as segmentation, forecasting, classification, regression, clustering, propensity modeling, or other statistical methods.
  • Translate ambiguous client or business asks into structured analytical approaches, assumptions, outputs, and timelines.
  • Build clear, client-ready deliverables in PowerPoint, Excel, dashboards, or other reporting formats.
  • Perform QA on data, code, methodology, and outputs to ensure accuracy and defensibility.
  • Support basic data engineering tasks such as dataset creation, data cleaning, feature generation, pipeline logic, and workflow automation.
  • Work with cloud-based data platforms, notebooks, compute servers, and shared analytics environments.
  • Mentor analysts and junior data scientists on SQL, Python, analytical methods, documentation, and quality control.
  • Partner with cross-functional teams across analytics, product, engineering, consulting, and client-facing functions. 

What You'll Bring

  • 5+ years of experience in data science, advanced analytics, healthcare analytics, life sciences analytics, analytics consulting, or a related quantitative role.
  • Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics, Public Health, or a related quantitative field.
  • Strong hands-on SQL experience, including complex joins, CTEs, aggregations, window functions, data validation, and performance-aware querying.
  • Strong hands-on Python experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, or similar tools.
  • Experience working with large, complex datasets and turning them into actionable insights.
  • Practical understanding of data science methods and when to apply them to business problems.
  • Basic understanding of data engineering concepts such as ETL/ELT, data pipelines, data models, data quality checks, and reusable workflows.
  • Experience working in cloud-based or server-based analytics environments such as Databricks, Snowflake, AWS, Azure, GCP, or similar platforms.
  • Strong communication skills with the ability to explain technical work to nontechnical stakeholders.
  • Ability to manage multiple priorities, work independently, and maintain strong attention to detail.

Preferred Qualifications 

  • Experience in healthcare, life sciences, pharma, medtech, payer/provider analytics, commercial analytics, or real-world evidence.
  • Experience with healthcare claims, EHR/EMR, provider, patient, HCP/HCO, prescribing, sales, market access, or similar datasets.
  • Experience with scripting, Git/version control, notebooks, scheduled jobs, or workflow automation.
  • Experience with Power BI, Tableau, Looker, Sigma, or similar BI tools.
  • Exposure to cloud data platforms, scalable compute environments, or production-oriented analytics workflows.

Compensation and Benefits


The salary range for this position is $107,100 - $160,000 per year, which represents the base pay the company reasonably and in good faith expects to pay for this role. Actual pay within this range will be determined based on factors such as relevant experience, skills, and qualifications. 

Depending on the position, employees may also be eligible to participate in a company bonus or commission plan. All employees are eligible for a comprehensive benefits package, including medical, dental, and vision coverage, unlimited paid time off, and participation in the company's 401(k) plan with employer contribution.