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Python Analytics Jobs in Buffalo, NY (NOW HIRING)

Danaher

Digital Analyst Internships

Buffalo, NY

$95.40K - $112.80K/yr

... like Google Analytics, PowerBI, Excel, and Looker Studio to extract actionable insights ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

FocusKPI

Marketing Operations Analyst

Buffalo, NY

Comfortable with Python. * Experience working within data platforms like Databricks/Snowflake, and analytics modeling platforms such as Tableau * Strong analytical and problem-solving skills with the ...

Osmose Utilities Services

GIS Analyst

Depew, NY · On-site

Osmose Utilities is currently seeking a GIS Analyst in our Depew, NY office able to work a HYBRID ... Working knowledge of geoprocessing scripts, preferably Python * Strong understanding of database ...

Osmose Utilities Services

GIS Analyst

Depew, NY · On-site

Osmose Utilities is currently seeking a GIS Analyst in our Depew, NY office able to work a HYBRID ... Working knowledge of geoprocessing scripts, preferably Python * Strong understanding of database ...

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How much do python analytics jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for python analytics in Buffalo, NY is $56.78, according to ZipRecruiter salary data. Most workers in this role earn between $46.83 and $64.52 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 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 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.

What are popular job titles related to Python Analytics jobs in Buffalo, NY? For Python Analytics jobs in Buffalo, NY, the most frequently searched job titles are:
What job categories do people searching Python Analytics jobs in Buffalo, NY look for? The top searched job categories for Python Analytics jobs in Buffalo, NY are:
What cities near Buffalo, NY are hiring for Python Analytics jobs? Cities near Buffalo, NY with the most Python Analytics job openings:
Python Analytics jobs near you
Credit Model Development Quantitative Analyst II - Small Business and Home Secured (Hybrid - see ...

Credit Model Development Quantitative Analyst II - Small Business and Home Secured (Hybrid - see ...

M&T Bank

Buffalo, NY • On-site

Full-time

Posted 14 days ago

M&T Bank rating

7.8

Company rating: 7.8 out of 10

Based on 179 frontline employees who took The Breakroom Quiz

65th of 141 rated banks

Job description

** Work Location/Arrangement: This is a hybrid position requiring in-office work four (4) days every week at an M&T office in Buffalo, NY, Bridgeport, CT, Wilmington, DE, Baltimore, MD, Washington, DC, or possibly NY, NY.
**If the final candidate is not near one of the attached locations, there might be a possibility for a remote arrangement.
Overview:
Provides analytical and technical support for the development, refinement, and ongoing monitoring of credit risk models used to meet regulatory requirements and support the Bank's strategic risk management objectives. This includes models for loss forecasting, default probability estimation, and other credit-sensitive behaviors across lending portfolios. Performs data preparation, exploratory data analysis, and model estimation under the guidance of senior modelers, leveraging strong quantitative skills and proficiency in Python, SQL, and statistical methods. Collaborates with Credit Risk Management, Model Risk Management, and business line partners to ensure model methodologies, assumptions, and outputs align with regulatory expectations and the Bank's broader credit risk framework. Communicates analytical results through clear narratives, visualizations, and documentation that support model development, validation activities, and ongoing performance monitoring.
Primary Responsibilities:
  • Support the development, enhancement, and testing of credit risk models, including probability of default, loss forecasting, risk rating, and other borrower-behavior models.
  • Conduct statistical and econometric analyses using Python, SQL, and related tools to estimate, validate, and refine model components.
  • Prepare, clean, and analyze large-scale loan and customer datasets, ensuring data quality and readiness for modeling.
  • Assist with model implementation and ongoing performance monitoring, identifying deviations and contributing to model improvements.
  • Develop and maintain clear, comprehensive model documentation and performance monitoring reports.
  • Communicate analytical findings through visualizations, presentations, and written summaries.
  • Collaborate with Credit Risk Management, Model Risk Management, and business partners to ensure model alignment with regulatory expectations.
  • Provide analytical support across the Bank and contribute to a collaborative, results-focused environment.

Scope of Responsibilities:
The position serves as a mid-level quantitative analyst responsible for applying statistical programming and analytical techniques to support the development, implementation, and maintenance of credit risk models. The analyst works with complex datasets and contributes to the creation of behavioral and credit-sensitive models. The role requires clear communication of findings through narratives, visualizations, and technical explanations. Success requires strong attention to detail, consistent execution, and the ability to manage multiple concurrent initiatives in collaboration with teams across the Bank. The analyst must be able to identify and interpret complex business, data, and statistical issues, contributing to solutions that enhance model performance and support broader risk management objectives.
Supervisory/Managerial Responsibilities:
Not Applicable
Education and Experience Required:
  • Bachelor's degree and a minimum of one year of proven quantitative behavioral modeling experience, or a combined minimum of five years of higher education and/or work experience, including at least one year of quantitative modeling experience.
  • Minimum of one year of on-the-job experience using statistical software packages such as SAS, Python, or R.
  • Strong Python skills required.
  • Model development experience required, including familiarity with logistic and linear regression techniques.
  • Minimum of one year of experience working in a data management environment such as SQL Server Management Studio.
  • Minimum of one year of experience managing and analyzing large datasets, with the ability to communicate results clearly using written, verbal, and visual formats.

Education and Experience Preferred:
  • Master's or Doctorate degree in Statistics, Economics, Finance, or a related quantitative field.
  • Minimum of two years of statistical analysis or programming experience.
  • Credit model development experience, with consumer, home secured, or small business modeling preferred.
  • One or more years of hands-on Python programming experience.
  • Proficiency in econometric and statistical techniques, including panel-data methods, and logistic regression.
  • Knowledge of model risk management and validation practices, including familiarity with SR 11-7 guidance.
  • Ability to work independently and collaboratively within a team environment.
  • Demonstrated leadership skills and a strong desire to learn and contribute to team objectives.

Physical Requirements:
None
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $71,600.00 - $119,300.00 Annual (USD). The successful candidate's particular combination of knowledge, skills, and experience will inform their specific compensation.
Location
Buffalo, New York, United States of America

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