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Python Data Analyst Jobs in Coppell, TX (NOW HIRING)

Brillio

Lead Data Analyst - R01568245

Dallas, TX

Spark - Pyspark, SQL, SQL (Basic + Advanced), Python, Hive, Data Modelling Fundamentals Specialization * Data Analysis: Analyst Job requirements * Product Analyst As a Product Analyst, you will drive ...

New

Lancesoft

Business Data Analyst

Plano, TX · On-site

$40 - $42/hr

... such as Python or R is highly desirable. • Understanding of data modeling concepts and ETL ... and analytical thinking abilities. • Collaborative mindset with a focus on teamwork and ...

Cliftonlarsonallen

Data Analyst Senior

Dallas, TX · On-site +1

$85K - $107K/yr

CLA is looking to hire a Data Analyst Senior; you will make use of the Microsoft Power Platform, or a scripting language like R or Python. The Data Analyst Senior cleans up data for analysis and/or ...

Brillio

Lead Data Analyst - R01568245

Dallas, TX · On-site +1

Spark - Pyspark, SQL, SQL (Basic + Advanced), Python, Hive, Data Modelling Fundamentals Specialization * Data Analysis: Analyst Job requirements * Product Analyst As a Product Analyst, you will drive ...

New

Service Experts

Sr. Data Analyst

Richardson, TX · On-site

$78K - $98K/yr

Expert proficiency in Python for data analysis and modeling * Strong experience with Databricks or similar distributed computing/cloud platform. * High proficiency in reporting tools (e.g., PowerBI)

Service Experts

Sr. Data Analyst

Richardson, TX · On-site

$78K - $98K/yr

Expert proficiency in Python for data analysis and modeling * Strong experience with Databricks or similar distributed computing/cloud platform. * High proficiency in reporting tools (e.g., PowerBI)

NCD

Senior Data Analyst

Dallas, TX · On-site

$85K - $107K/yr

Summary NCD is seeking a Sr. Data Analyst to join our Data team as a strong mid-level individual ... Python or scripting experience is helpful, especially for automation, QA, or data validation, but ...

Critical Propulsion

Senior Data Analyst

Dallas, TX · On-site

$85K - $107K/yr

You write Python, SQL, and Spark to manipulate, analyze, and automate. You\'re not just a GUI modeler. You write code to solve data problems. * You define and enforce data modeling standards. You ...

AT&T

Lead Data Analysis

Dallas, TX · On-site

The ideal candidate combines strong data analysis skills, SQL and Python capability, executive storytelling, project management discipline, and hands-on experience or strong working knowledge of ...

Orion180

Senior Insurance Data Analyst

Irving, TX · On-site

$82K - $104K/yr

Leverage Python, SQL, and statistical analysis to identify key data patterns and multivariate correlations. * Conduct exploratory data analysis and ensure data integrity across structured and ...

Ascot Group

Actuarial Data Analyst, Captives

Dallas, TX · On-site

Use R, Python, and SQL to build data pipelines and reports to monitor portfolio health * Normalize ... Work with actuarial partners in building analytical tools to support underwriters * Assist with ad ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Coppell, TX

Python Data Analyst information

See Coppell, TX salary details

$31.4K

$76.3K

$125.5K

How much do python data analyst jobs pay per year?

As of Jul 12, 2026, the average yearly pay for python data analyst in Coppell, TX is $76,291.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,700.00 and $89,500.00 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.
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Python Data Analyst jobs near you
Lead Data Analyst - R01568245

Lead Data Analyst - R01568245

Brillio

Dallas, TX

Other

Posted 2 days ago

New

Job description

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work certification year after year.

Lead Data Analyst
Primary Skills
  • Spark - Pyspark, SQL, SQL (Basic + Advanced), Python, Hive, Data Modelling Fundamentals
Specialization
  • Data Analysis: Analyst
Job requirements

  • Product Analyst 

    As a Product Analyst, you will drive data-informed product decisions by delivering actionable insights, designing robust experiments, and deeply understanding user behavior. You will partner closely with Product, UX, and Engineering to shape product strategy and improve customer experience across security products. 

    Key Responsibilities 

                    Lead experimentation strategy: Design, execute, and analyze A/B tests and quasi-experiments to evaluate product and feature impact on engagement, retention, and customer satisfaction.  

                    Drive product insights: Conduct deep-dive analyses on user journeys, onboarding funnels, feature adoption, and retention cohorts to identify growth and optimization opportunities.  

                    Define and operationalize metrics: Establish north-star metrics, KPIs, and guardrails; ensure consistent definitions across teams and dashboards.  

                    Enable product decision-making: Translate complex analyses into clear, actionable recommendations for product roadmaps and prioritization.  

                    Improve data foundations: Partner with data engineering and platform teams to ensure high-quality telemetry, scalable data models, and reliable reporting layers.  

                    Leverage advanced analytics: Apply statistical techniques (segmentation, cohort analysis, regression, causal inference) to uncover drivers of user behavior and product performance.  

                    Collaborate cross-functionally: Work closely with Product Managers, Designers, and Engineers to embed analytics into the product development lifecycle.  

                    Mentor and elevate analytics practices: Guide analysts on experimentation design, metric definition, and storytelling best practices.  

                    Communicate effectively: Deliver clear, compelling insights to stakeholders and leadership through dashboards, presentations, and narratives.  

    About You 

                    5-8 years of experience in product analytics, advanced analytics, or data science with strong product focus.  

                    Strong experimentation expertise: Hands-on experience designing and interpreting A/B tests and quasi-experimental methods (e.g., difference-in-differences, matching).  

                    Advanced analytical skills: Proficient in SQL and Python for data analysis; strong foundation in statistics and hypothesis testing.  

                    Product analytics experience: Deep understanding of user behavior analysis, funnel optimization, retention, and feature adoption metrics.  

                    Data visualization & storytelling: Experience with BI tools such as Power BI, Tableau, or Looker to communicate insights effectively.  

                    Telemetry & data modeling knowledge: Experience working with event-based data and defining tracking for digital products.  

                    Business and product acumen: Ability to connect data insights into product strategy and customer experience improvements.  

                    Strong communication and stakeholder management skills, with the ability to influence decisions across teams.  

                    Bachelor's or master's degree in a quantitative field a plus (Statistics, Computer Science, Engineering, Mathematics, or related) 

#LSR1
$100 - $105 a year
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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