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Intern Data Analyst R Programming Jobs in Texas (NOW HIRING)

... push engineering teams on data quality and pipeline reliability, and represent your findings to ... Proficiency in Python or R for analysis and automation is a plus. • Strong instincts for ...

... noSQL, Python, R, Javascript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.) Experience developing ...

Python, R/Shiny, Tableau, Power BI * Experience with SQL and other modern data storage technologies ... Fluent in SQL * Ability to work independently with minimal Engineering support * Extensive ...

... engineers of the Data Science & Tools Team to analyze Samsung's deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such ...

The Data Analyst is responsible for creating & providing correct, accurate & complete data ... Knowledge of DAX, T-SQL, C#, D3, R or Python or any other statistical programming language for ...

The Data Analyst is responsible for creating & providing correct, accurate & complete data ... Knowledge of DAX, T-SQL, C#, D3, R or Python or any other statistical programming language for ...

Partner with Engineering, Data Science, and other teams to identify and use the data needed to ... Proficiency in either SQL, Python, or R conducting complex analyses on large datasets * Working ...

The Data Analyst is responsible for creating & providing correct, accurate & complete data ... Knowledge of DAX, T-SQL, C#, D3, R or Python or any other statistical programming language for ...

Programming (Python/R): Proficiency in Python (Pandas, NumPy) or R for statistical analysis and automation is standard. * Data Visualization: Experience with Tableau, Looker (LookML), or Power BI to ...

Programming (Python/R): Proficiency in Python (Pandas, NumPy) or R for statistical analysis and automation is standard. * Data Visualization: Experience with Tableau, Looker (LookML), or Power BI to ...

Programming (Python/R): Proficiency in Python (Pandas, NumPy) or R for statistical analysis and automation is standard. * Data Visualization: Experience with Tableau, Looker (LookML), or Power BI to ...

Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience in statistical software, such as R, SAS, or Python. Proven experience leading and managing cross ...

Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience in statistical software, such as R, SAS, or Python. Proven experience leading and managing cross ...

SIMILAR CAREER TITLESBusiness Analyst, Data Scientist, Data Engineer, Financial Analyst, Marketing ... Knowledge of Python or R * Familiarity with machine learning * Understanding of ETL processes

Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience in statistical software, such as R, SAS, or Python. Proven experience leading and managing cross ...

SIMILAR CAREER TITLES Business Analyst, Data Scientist, Data Engineer, Financial Analyst, Marketing ... Knowledge of Python or R * Familiarity with machine learning * Understanding of ETL processes

... programming, statistical analysis and data modeling • Extensive experience in statistical software, such as R, SAS, or Python. • Proven experience leading and managing cross-functional teams to ...

Showing results 21-40

Intern Data Analyst R Programming information

What is the difference between Intern Data Analyst R Programming vs Intern Data Analyst Python?

AspectIntern Data Analyst R ProgrammingIntern Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentData analysis, statistical modeling, research projectsData analysis, automation, machine learning tasks
Industry UsageResearch, healthcare, financeTech, finance, marketing

Both roles are entry-level internships focused on data analysis, requiring programming skills in their respective languages. R is often used for statistical analysis and visualization, while Python is versatile for data manipulation and machine learning. The choice depends on the industry and specific project needs.

What are the most commonly searched types of Data Analyst R Programming jobs in Texas?

The most popular types of Data Analyst R Programming jobs in Texas are:

Full-time

Re-posted 8 days ago


Job description

Role : Data Analyst
Location : Richardson, TX (Hybrid)
Key Skills:
  • Must be proficient in using AI
  • Experience with commercial real estate data
  • Able to present and communicate ideas to C-suite executives
  • Software skills: Proficiency with Microsoft Office tools (Word, Excel, Outlook, PowerPoint) and familiarity with modern analytics and data warehousing platforms (e.g., Snowflake, Databricks)

Job Description:
As a Data Analyst on the Advisory Data & Research team, you'll own analytical workstreams end-to-end, partner closely with a scrum team, and sit at the intersection of data, technology, and the business. You'll be close to the data - and close to the users - shaping what gets measured and why.
This isn't a reporting-factory role. You'll help frame the questions and define the methodology. You will drive the analysis, and be accountable for the insights. You'll partner with UX designers and product managers to embed analytics people actually use, push engineering teams on data quality and pipeline reliability, and represent your findings to business leaders and D&T leadership alike.
What You'll Do
• Own analytical workstreams end-to-end - synthesize input from users, business stakeholders, and D&T leadership into a clear, prioritized set of questions to answer and metrics to track.
• Build, maintain, and refine dashboards, reports, and self-service analytics: write clean, well-documented SQL, groom data backlogs, lead refinement sessions with stakeholders, and actively participate in scrum ceremonies, demos, and lead user testing and rollout of analytical products.
• Drive data discovery alongside Product and UX partners - conduct user research on analytical needs, run feedback sessions, and champion the end-user perspective in every metric and visualization decision.
• Translate business questions into execution by collaborating closely with Engineering and Data Engineering, turning analytical requirements into well-modeled, reliable, queryable data.
• Define and deliver specific analyses end-to-end, from problem framing through validation, presentation, and measurement of impact.
• Represent your analysis to business leadership and D&T leadership - providing crisp, regular readouts and connecting day-to-day work to broader strategic goals.
• Spot data quality problems before they become blockers: proactively investigate anomalies, resolve issues, and communicate with clarity and urgency when it matters.
What You'll Need
• 3-5+ years of experience in Data Analytics, Business Intelligence, Business Analytics, or a related quantitative field - with a track record of delivering analyses that influenced decisions. A bachelor's degree in a quantitative discipline is preferred; relevant experience counts.
• Strong SQL skills with hands-on experience querying large, complex datasets, plus fluency building dashboards and reports in modern BI tools (Power BI, Tableau, Looker, or similar). Proficiency in Python or R for analysis and automation is a plus.
• Strong instincts for prioritization - you know which questions matter, and you know how to explain why.
• The communication skills to work across levels: from a debugging session with a data engineer to a C-suite readout, you adjust your style and land your message.
• A bias for the truth - you ask hard questions of the data, validate your assumptions, and let what you find change your mind.
• Comfort navigating ambiguity, managing competing priorities, and keeping work focused when requirements shift.
• Proficiency with Microsoft Office tools (Word, Excel, Outlook, PowerPoint) and familiarity with modern analytics and data warehousing platforms (e.g., Snowflake, Databricks).
• Experience with data modeling, data quality, and data governance - you understand data and how it interacts with products and decisions.
• Experience in Commercial Real Estate (nice to have)