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Python Analytics Jobs in Massachusetts (NOW HIRING)

Sonsoft Inc

Lead Python Consultant

Boston, MA

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 ...

TriOptus LLC

Python Full Stack Developer

Boston, MA · Hybrid

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 ...

Worldpay

Senior Python Software Engineer

Boston, MA

$119K - $179K/yr

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 ...

Worldpay

Senior Python Software Engineer

Boston, MA · Remote

$119K - $179K/yr

We're looking for a Senior Python Engineer to join our ever evolving Pazien team and help us ... You'll be joining a small team working on expanding a new reporting and analytics product to ...

CarGurus

Business Analytics Analyst

Boston, MA

Data modeling; dbt, SQL, Python, Snowflake, and/or AWS; Business intelligence reporting and strategic analysis; Process automation and scripting; Data analysis, visualization techniques, and ...

Athenahealth

Manager, Analytics & Insights

Boston, MA

$99K - $167K/yr

The team partners with Product, Finance, Operations, and HR stakeholders and uses tools such as SQL, Python, Excel, BI platforms, and Snowflake to support analysis and reporting. The team values ...

IQVIA

Associate Director, Data Analytics

Boston, MA · Remote

The Associate Director of Data Analytics provides technical and people leadership to design, build ... Strong SQL + Python (or equivalent) delivering production-grade pipelines and automation.

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All JobsPython Analytics JobsPython Analytics Jobs in Massachusetts

Python Analytics information

What is the salary of a Python analyst?

The salary of a Python analyst typically ranges from $60,000 to $110,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, machine learning, and proficiency in tools like Pandas and Jupyter Notebook tend to earn higher salaries.

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.

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.

Can I be a data analyst in 3 months?

Becoming a data analyst with a focus on Python typically requires several months of dedicated learning, including skills in data manipulation, visualization, and tools like pandas and SQL. While some individuals may acquire foundational skills in three months, gaining proficiency for a professional role usually takes longer and depends on prior experience and learning pace.

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 still in demand?

Python analytics roles remain highly in demand due to Python's versatility in data analysis, machine learning, and automation. Employers seek professionals skilled in libraries like Pandas, NumPy, and frameworks such as TensorFlow, often requiring proficiency in data visualization and scripting. Staying updated with Python versions and related tools enhances job prospects in this field.

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 are popular job titles related to Python Analytics jobs in Massachusetts? For Python Analytics jobs in Massachusetts, the most frequently searched job titles are:
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:
Python Analytics jobs near you
Infographic showing various Python Analytics job openings in Massachusetts as of June 2026, with employment types broken down into 87% Full Time, 6% Part Time, 2% Temporary, and 5% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Lead Software Engineer (Python)

Prophecy Technologies

Boston, MA • On-site

Full-time

Posted 18 days ago

Job description

Role Summary
As a Lead Software Engineer (Python) at Trivelta, you will play a pivotal role in designing, developing, and scaling the platform's core backend infrastructure. This is a hands-on technical leadership position responsible for driving innovation, ensuring system performance, and maintaining high standards of security, compliance, and reliability.
You will collaborate closely with product, security, compliance, finance, and data analytics teams to build robust, scalable solutions in a highly regulated environment.
Key Responsibilities
Backend Architecture & Development
  • Architect and develop scalable, high-performance backend systems using Python.
  • Design and maintain robust APIs supporting mobile, web, and third-party integrations.
  • Drive best practices in backend design, code quality, and system reliability.

Performance, Security & Compliance
  • Optimize system performance, scalability, and availability.
  • Implement security best practices and ensure compliance with:
  • AML, KYC
  • Data privacy regulations
  • State-by-state sweepstakes regulations
  • Partner with compliance and security teams to meet regulatory standards.

Data & Analytics Infrastructure
  • Design and maintain data pipelines supporting:
  • Analytics and reporting
  • Fraud detection
  • Geolocation-based access controls
  • Regulatory and audit reporting

Technical Leadership
  • Lead and mentor engineers, promoting best practices and continuous learning.
  • Drive architectural decisions and long-term technical strategy.
  • Evaluate emerging technologies in fintech, gaming, and AI-based fraud detection.

Cross-Functional Collaboration
  • Work closely with product, finance, compliance, and support teams to translate business needs into technical solutions.
  • Ensure seamless system integration and operational efficiency.

Operational Excellence
  • Lead incident response for production outages or security events.
  • Implement proactive monitoring and alerting.
  • Perform root cause analysis and drive long-term corrective actions.

Required Skills & Qualifications
  • Proven experience designing and scaling high-performance backend systems.
  • Strong hands-on expertise in Python for backend development, automation, and data processing.
  • Experience building and maintaining RESTful APIs.
  • Strong knowledge of CI/CD pipelines and infrastructure automation.
  • Demonstrated ability to lead, mentor, and influence technical direction.
  • Experience working cross-functionally with product, finance, and compliance teams.
  • Solid understanding of:
  • System performance tuning
  • Security best practices
  • Regulatory compliance (AML, KYC, data privacy)

Preferred Qualifications
  • Experience with data pipelines, analytics platforms, and fraud detection systems.
  • Exposure to geolocation-based access controls.
  • Background in fintech, gaming, or regulated platforms.

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