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Python Analytics Jobs (NOW HIRING)

challenger

Data Warehouse Analytics Specialist

Sandy, UT · On-site

$17 - $21.75/hr

This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge ...

challenger

Data Warehouse Analytics Specialist

Sandy, UT

$17 - $21.75/hr

This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge ...

MeUndies

Manager, Analytics

Culver City, CA · On-site

$100K - $130K/yr

SQL, Python * Analytics Platforms: Tableau (advanced proficiency preferred), Google Analytics Bonus Points * BS/MS in Statistics. * Tableau Desktop and Tableau Cloud/Server expertise, including ...

Infojini Inc

Linux Systems Engineer

Washington, DC

Centrify, LDAP, Kerberos and Active Directory Scripting using Python Analytics Computing: SAS, R, Stata, MatLab Additional Information All your information will be kept confidential according to EEO ...

Conch Technologies Inc

RPA Developer

Orlando, FL · On-site

Develop automation scripts and logic using Python * Support analytics and data workflows using tools such as Alteryx, Snowflake, Tableau, and Power BI * Collaborate with project managers and ...

Apex Systems

Python Developer

Chandler, AZ · On-site

$51.25 - $70.75/hr

Analyze existing Perl code to translate business logic into Python. * Engage with developers and operational partners to ensure functionality meets requirements. * Contribute to the framework ...

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Python Analytics information

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How much do python analytics jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for python analytics in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

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.
More about Python Analytics jobs
What cities are hiring for Python Analytics jobs? Cities with the most Python Analytics job openings:
What states have the most Python Analytics jobs? States with the most job openings for Python Analytics jobs include:
What job categories do people searching Python Analytics jobs look for? The top searched job categories for Python Analytics jobs are:
Python Analytics jobs near you
Infographic showing various Python Analytics job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Python Analytics Developer

Python Analytics Developer

SIAL TECHNOLOGY PARTNERS

Nashville, TN • On-site

$48.50 - $67/hr

Other

Re-posted 25 days ago

Job description

Python Analytics Developer

Nashville, TN (on-site consultant role)

Hybrid 3~4 days in-office 8am 4pm CST workday.

Job Role:

Create and refine quant algorithm scripts in Python to solve complex financial problems.

Close to a Data Science Engineer type of role.

Technical Skills:

  • Strong knowledge of Python programming language and its frameworks, with a focus on back-end development.
  • Knowledge of software development principles and Object-Oriented development and design patterns (C# experience a plus)
  • Experience with back-end technologies such as Oracle, SQL Server, .NET, REST API, microservices, etc.
  • Understanding of parallel programming concepts and packages parallelization/multiprocessing/cloud.
  • Working experience/knowledge of Azure is a plus (CI/CD, Kubernetes, Data Factory, Containers/Pods/Docker, [ AWS is ok - Azure equivalent ]

Quantitative and Analytical Skills:

  • Strong mathematical and statistical skills, with the ability to apply them to develop financial algorithms.
  • Experience in developing and optimizing quantitative algorithms for financial applications.
  • Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex problems.
  • Ability to troubleshoot and optimize existing analytics solutions for improved performance.

Investment Product

- Tax Advantaged Taxable Bond SMAs (differentiate our Taxable SMAs with an industry first systematic tax optimization for taxable bonds)

- Capacity to develop additional Taxable SMA products (potentially offshore solutions, completion fund products, non-USD, etc)

Type of Quant/Algo/Analytic Software to Develop

  • Automated Transition Analysis (real-time transition from existing bonds to portfolios via Service Center)
  • Automated Proposals (cash funded proposals/model portfolios via Service Center)
  • Trade Rationales (unparalleled transparency for advisors into SMA trading activity and benefits)
  • Transition Scorecards (proactive touch point summarizing onboarding process and portfolio changes/benefits)

We look forward to reviewing your profile.

Thanks, Talent Team @ SIALTP

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