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Senior Python Data Analysis Jobs in Garner, NC (NOW HIRING)

Sarian, Inc.

Sr. Data Analyst

Cary, NC · On-site

$81.90K - $103.30K/yr

End to End Solution Architect with experience in data and report requirement analysis/understanding ... Senior BSA with over 10+ years' work experience as an analyst is preferred. Muralikrishna Sarian ...

GFT.

Senior GIS Analyst

Raleigh, NC

$90K - $115K/yr

Dashboard development for data analysis and situational awareness. * Configure and deploy field ... Production experience with Python and ArcGIS API for Python and ArcPy. * Production experience with ...

Kanak Elite Services Inc

Data and AI Analyst

Cary, NC · On-site

... data analysis, AI modeling, or business intelligence tools. • Experience with SAS Viya, especially SAS Visual Analytics and Model Studio, is highly preferred. • Familiarity with Python, R, SQL ...

Sarian, Inc.

Senior Data Analyst

Cary, NC · On-site

$79.70K - $100.50K/yr

Excellent in • Communication • Problem solving and Root cause Analysis Job responsibilities ... Senior BSA with over 10+ years' work experience as an analyst is preferred.

RELX Group plc

Senior Data Scientist II

Raleigh, NC · On-site

$104.90K - $174.70K/yr

We are seeking a Senior Data Scientist II to help lead the design and validation of AI-driven ... Proficiency in Python and data analysis tools. * Strong foundation in statistics, modeling, and ...

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All JobsPython Data Analysis JobsSenior Python Data Analysis JobsSenior Python Data Analysis Jobs in Garner, NC

Senior Python Data Analysis information

See Garner, NC salary details

$49K

$126.6K

$173.8K

How much do senior python data analysis jobs pay per year?

As of Jun 1, 2026, the average yearly pay for senior python data analysis in Garner, NC is $126,554.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,300.00 and $145,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Python Data Analyst, and why are they important?

To thrive as a Senior Python Data Analyst, you need an in-depth understanding of data analysis, statistical modeling, and advanced Python programming, typically supported by a degree in a quantitative field. Proficiency with data analysis libraries (like pandas, NumPy, and SciPy), visualization tools (such as Matplotlib and Seaborn), and experience with SQL databases are essential, and certifications like Microsoft Certified: Data Analyst Associate can be beneficial. Strong problem-solving abilities, effective communication, and the capacity to distill complex data insights for stakeholders are critical soft skills. These competencies enable you to extract actionable insights from large datasets, drive data-informed decision-making, and collaborate effectively across teams.

What are some common challenges Senior Python Data Analysts face when working with large datasets, and how can they overcome them?

Senior Python Data Analysts often encounter difficulties such as slow processing speeds, memory limitations, and data quality issues when handling large datasets. To overcome these challenges, it's essential to leverage efficient libraries like pandas and Dask, utilize optimized data formats (such as Parquet), and implement batch processing or cloud-based solutions. Collaborating closely with data engineers and IT teams also helps ensure robust data pipelines and infrastructure. Regular code optimization and staying updated on best practices can further enhance performance when working at scale.

What is a Senior Python Data Analyst?

A Senior Python Data Analyst is an experienced professional who uses Python programming to collect, process, and analyze large sets of data. They are responsible for extracting meaningful insights from data to support business decisions, often using libraries like pandas, NumPy, and matplotlib. In addition to technical skills, they also apply statistical analysis and data visualization techniques, and frequently mentor junior analysts or collaborate with data scientists and engineers. Their role may also involve developing automated data pipelines and ensuring data quality across projects.

What is the difference between Senior Python Data Analysis vs Data Scientist?

AspectSenior Python Data AnalysisData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentData analysis teams, business unitsResearch, product development, analytics teams
Industry UsageBusiness intelligence, finance, marketingTech, healthcare, finance, research
CertificationsPython certifications, data analysis coursesData science certifications, machine learning courses

While both roles involve Python and data handling, Senior Python Data Analysts focus on interpreting data and creating reports for business decisions, whereas Data Scientists develop predictive models and advanced algorithms to extract deeper insights. The roles often overlap, but Data Scientists typically require broader skills in machine learning and statistical modeling.

What job categories do people searching Senior Python Data Analysis jobs in Garner, NC look for? The top searched job categories for Senior Python Data Analysis jobs in Garner, NC are:
Senior Python Data Analysis jobs near you
Sr. Manager, Finance Data & Analytics

Sr. Manager, Finance Data & Analytics

Couchbase, Inc.

Raleigh, NC

Other

Posted 3 days ago

Job description

Job Description: Sr Manager, Finance Data & AnalyticsAbout the Job

As the Sr Manager of Finance Data & Analytics, you lead the engine room that powers our strategic decision-making. Your success is defined by the winning combination of partnering your team's technical data expertise with the business context of our other Finance functions to maximize insights for the executive team. You are responsible for delivering data analytics and the high-confidence Analyst-Ready Data Layer, ensuring our organization executes on insights.

Key Responsibilities
  • Data Analysis & Insights: Lead high-impact, cross-functional analyses to uncover the why behind business results, identifying hidden trends and providing strategic recommendations across both top-line growth and expense management.
  • Predictive Analytics: Develop and refine early warning indicators that signal structural risks or opportunities in the long-term outlook before they hit the P&L.
  • Executive Decision Support: Synthesize complex data analytics into clear, actionable narratives for the CEO, CFO, and PE partners, acting as a strategic advisor to the VP of Finance & Strategy.
  • Partnerships & Insights: Actively partner with the Finance & Strategy team on high-priority projects, combining deep data mining with functional business context to deliver more impactful insights.
  • Analyst-Ready Data Layer: Build and govern a dedicated business data layer, utilizing both structured warehouse schemas and agile ad-hoc tables, to provide a foundational data layer that eliminates manual data prep, allowing every analyst to work efficiently.
  • Connected Planning:  Oversee the integrated architecture of our planning environment (Pigment), ensuring that functional models remain synchronized without sacrificing the autonomy of individual teams.
  • Finance AI & Innovation Roadmap: Act as the Finance lead for emerging AI/ML technologies in the finance space; evaluate and pilot AI-driven concepts to enhance forecasting capabilities, automate data anomaly detection, and streamline the Analyst-Ready data layer as the technology matures.
The Profile
  • Strategic Partner: 8-10+ years in Finance or Analytics at a $100M+ SaaS company, with a mastery of recurring revenue economics, customer lifecycles, and the data structures required to model complex subscription metrics.
  • Bridge Builder: Exceptional at communicating technical data concepts to non-technical audiences.
  • Technological Curiosity: A forward-thinking mindset regarding the evolution of technology and Finance; you have a pulse on how Generative AI and Machine Learning are transforming data analysis and can pragmatically apply these tools to solve business problems.
  • Data Supported Rigor: You thrive in environments where data accuracy, auditable definitions, and analytical integrity are the standard.
  • Advanced SQL & Solution Design: High proficiency in advanced SQL for complex data manipulation to ensure a robust business data layer. 
  • Data Governance & Quality:  Proven ability to implement data hygiene protocols and traceability in the transformation layer to guarantee that financial outputs are valid and audit-ready.
  • DWH Partnership: Deep experience partnering with Data Engineering and Data Warehouse teams to influence data ingestion priorities and schema designs that support scalable financial modeling.

Analytical Storytelling: Expert at using tools like Tableau to turn the engineered data layer into compelling narratives for leadership.

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