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Senior Python Data Analysis Jobs in Connecticut (NOW HIRING)

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Senior Data Analyst

Stamford, CT · On-site +1

$91K - $115K/yr

Conduct exploratory data analysis to uncover hidden patterns, correlations, and insights within ... Proficiency in SQL and experience querying relational databases; familiarity with dbt and Python is ...

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Senior Data Analyst

Stamford, CT · Remote

$91K - $115K/yr

Conduct exploratory data analysis to uncover hidden patterns, correlations, and insights within ... Proficiency in SQL and experience querying relational databases; familiarity with dbt and Python is ...

ALIS Software LLC

Senior Data Analyst

Windsor, CT · On-site

$85K - $107K/yr

Perform deep-dive data analysis to identify business opportunities, risks, and performance drivers ... Present insights and recommendations to senior leadership in a clear, concise manner. * Contribute ...

Gartner

Sr Data Analyst (SQL, Chief Data Office)

Stamford, CT · Hybrid

$91K - $115K/yr

Gartner is seeking a Senior Data Analyst within the Chief Data and Analytics Office. Data Analysts ... Advanced proficiency in SQL; understanding of data analysis tools and techniques; Python skills a ...

Customer Operations

Senior Data Analyst

Stamford, CT · On-site +1

$86K - $152K/yr

As a Senior Data Analyst on Spectrum's Customer Service Reliability team you'll help shape the ... Lead advanced analysis that informs strategic priorities, improves operational performance, and ...

The Hartford

Sr Staff Data Engineer

Hartford, CT · Hybrid

... Python, SQL, PL/SQL), and experience with DevOps / DataOps pipelines, cloud platforms (AWS services ... Collaborate with data analysts, data scientists, and BI teams to build data models and pipelines ...

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Senior Python Data Analysis information

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 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 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 are the most commonly searched types of Python Data Analysis jobs in Connecticut? The most popular types of Python Data Analysis jobs in Connecticut are:
What are popular job titles related to Senior Python Data Analysis jobs in Connecticut? For Senior Python Data Analysis jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Senior Python Data Analysis jobs in Connecticut look for? The top searched job categories for Senior Python Data Analysis jobs in Connecticut are:
What cities in Connecticut are hiring for Senior Python Data Analysis jobs? Cities in Connecticut with the most Senior Python Data Analysis job openings:
Senior Python Data Analysis jobs near you

Python Data Engineer

Texas State Library and Archives Commision

Hartford, CT • On-site

$115K - $138K/yr

Contractor

Posted 11 hours ago

Job description

Job Description:
We are looking for a skilled Python Data Engineer with hands-on experience in Azure, PySpark, and Databricks, specifically within the insurance domain. This is a hybrid, long-term contract position requiring a mix of remote and onsite work in either Hartford, CT or Charlotte, NC. The ideal candidate will be responsible for building, optimizing, and maintaining data pipelines and supporting data-driven decision-making across the organization.
Key Responsibilities:
  • Design and develop scalable and robust data pipelines using PySpark and Python.
  • Leverage Azure Data Services (e.g., Azure Data Factory, Azure Data Lake, Azure Synapse) for data integration and transformation.
  • Utilize Databricks for distributed data processing, data wrangling, and advanced analytics.
  • Ensure data quality, integrity, and compliance with data governance and security policies.
  • Collaborate with cross-functional teams, including business analysts, data scientists, and application developers.
  • Participate in performance tuning, troubleshooting, and optimization of data workflows.
  • Translate business requirements into technical specifications, especially within the insurance industry context.
  • Develop and maintain documentation for data pipelines and architecture.

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