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Python Data Analyst Jobs in Buffalo, NY (NOW HIRING)

Analyze large scale complex business data (time series data, structured/unstructured) from various ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

New

Data Quality Lead Analyst

Getzville, NY · On-site

$125K - $131K/yr

Excel, VBA, MS Access, SQL, Tableau and Python; Ad-hoc reporting for senior management; and Project Management for data analytics initiatives. Applicants submit resumes at Please reference Job ID ...

New

Senior Media Analyst

Boston, NY

$83K - $110K/yr

Strong proficiency in data analysis, modeling, and visualization tools (e.g., Excel, Power BI/Tableau, SQL, Python) for data extraction, transformation, analysis, and workflow automation * Hands-on ...

Design and develop product prototypes based on financial and travel spend analysis and client data. * Utilize Python, R, JavaScript, or Tableau to build scalable, testable tools for customers.

EHS Data Manager

Buffalo, NY · On-site

$80K - $109K/yr

Strong foundational knowledge of data analysis concepts and techniques. * At least five (5) years of experience with tools such as: * SQL and Python * ETL processing * Data warehousing, datalake and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... Python and SQL - Experience with Docker and containerized deployments - Skilled in AI techniques ...

EHS Data Manager

Buffalo, NY · Hybrid

$80K - $109K/yr

Strong foundational knowledge ofdata analysis concepts and techniques. * At least five (5) years of experience with tools such as: * SQL and Python * ETL processing * Data warehousing, datalake and ...

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Python Data Analyst information

See Buffalo, NY salary details

$32.9K

$80.1K

$131.7K

How much do python data analyst jobs pay per year?

As of Jul 18, 2026, the average yearly pay for python data analyst in Buffalo, NY is $80,051.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,500.00 and $94,000.00 per year, depending on experience, location, and employer.

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.
What are the most commonly searched types of Python Data Analyst jobs in Buffalo, NY? The most popular types of Python Data Analyst jobs in Buffalo, NY are:
What are popular job titles related to Python Data Analyst jobs in Buffalo, NY? For Python Data Analyst jobs in Buffalo, NY, the most frequently searched job titles are:
What job categories do people searching Python Data Analyst jobs in Buffalo, NY look for? The top searched job categories for Python Data Analyst jobs in Buffalo, NY are:
What cities near Buffalo, NY are hiring for Python Data Analyst jobs? Cities near Buffalo, NY with the most Python Data Analyst job openings:
Infographic showing various Python Data Analyst job openings in Buffalo, NY as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 81% Full Time, 11% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $80,051 per year, or $38.5 per hour.

Full-time

Posted 2 days ago

New


Job description

We are looking for the right people people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the worlds largest providers of products and services to the global energy industry.

Job Description & Responsibilities:
Data Scientist under general supervision will perform data engineering, data modeling and model deployment.
Analyze large scale complex business data (time series data, structured/unstructured) from various data sources and draw insights
Leverage common open-source Machine Learning/Deep Learning packages for identifying data patterns and/or building predictive models
Conduct statistical analysis to determine trends and significant data relationships
Keep up to date with latest Machine Learning and Artificial Intelligence advancements
Work with data engineers to design and construct data pipelines for reproducible analysis
Leverage cloud computing technologies like Microsoft Azure and distributed computing technologies like Apache Spark
Present results of analyses, including design of graphs, charts, tables, and other data visualizations

Qualifications:
Industry experience in predictive modeling, data science and analysis.
Knowledge of Machine Learning frameworks and packages, including Keras, TensorFlow, Scikit-Learn and cloud computing platforms like Azure.
Experience handling terabyte size datasets, diving into data to discover hidden patterns and using data visualization tools.
Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.
Demonstrated teamwork, strong communication skills, and collaborative in complex engineering projects.
Completion of an undergraduate degree in STEM. Master's degree in STEM is preferred.

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.