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Intern Python Data Analyst Jobs in Pennsylvania (NOW HIRING)

Senior Data Analyst

Philadelphia, PA · On-site

$86K - $109K/yr

SQL, Python, R). * Strong data analysis skills, with the ability to synthesize data, identify and highlight trends, assess business impacts, and make recommendations for improvement. * Excellent ...

Senior Data Analyst

Philadelphia, PA · On-site +1

$86K - $109K/yr

The Data & Analytics team consists of data analysts, data engineers and analytics engineers working ... Experience with R or Python for creating data models or data manipulation * The ability to make ...

Senior Data Analyst

Conshohocken, PA · On-site

$84K - $106K/yr

The Senior Data Analyst demonstrates analytical thinking and creative problem solving for business ... SQL (preferred), dbt, DAX, Python or equivalent. * Experience with Snowflake or an equivalent cloud ...

Our work includes data preparation and transformation, discovery analysis, experimental design ... Proficiency in SQL, Tableau, Python, PySpark and cloud platforms like AWS and Snowflake.

Our work includes data preparation and transformation, discovery analysis, experimental design ... Proficiency in SQL, Tableau, Python, PySpark and cloud platforms like AWS and Snowflake.

Working knowledge of Python or R for analysis and data wrangling (advanced modeling not required) * Experience working with data from CRM systems, e.g., Salesforce * Familiarity with underwriting and ...

Experience working with structured data using a modern scripting language, preferably R, Python, SQL or SAS. Compensation The listed annualized base pay range is primarily based on analysis of ...

Senior Data Analyst

Fort Washington, PA · On-site

$82K - $104K/yr

Proficient in SQL, Python/R, Excel, and BI tools (e.g., Tableau, Power BI). Experience with data ... A meticulous approach to data analysis with a high level of accuracy and attention to detail.

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Intern Python Data Analyst information

What does an Intern Python Data Analyst do?

An Intern Python Data Analyst assists in collecting, processing, and analyzing data using Python programming language. They support the data team by writing scripts to clean and visualize data, and help generate insights from large datasets. Interns also learn to use data analysis libraries such as pandas, NumPy, and matplotlib, and may assist with reporting or automation tasks. This role is typically entry-level and offers hands-on experience in data analysis within a supervised environment.

What is the difference between Intern Python Data Analyst vs Intern Data Scientist?

AspectIntern Python Data AnalystIntern Data Scientist
Required SkillsPython, SQL, Excel, Data VisualizationPython, R, Machine Learning, Statistical Analysis
Work EnvironmentData analysis, reporting, dashboardsModel development, predictive analytics, research
Industry UsageBusiness intelligence, finance, marketingTech, healthcare, research institutions

Intern Python Data Analysts focus on analyzing data, creating reports, and visualizations using Python and related tools. Intern Data Scientists work on building models, applying machine learning, and conducting advanced statistical analysis. While both roles require Python skills, Data Scientists typically need additional knowledge of R and machine learning techniques. The roles often overlap in industries like tech and finance, but Data Scientists tend to engage in more complex predictive tasks, whereas Data Analysts focus on interpreting data for business insights.

What types of projects and tasks can an Intern Python Data Analyst expect to work on during their internship?

As an Intern Python Data Analyst, you can expect to work on a variety of data-driven projects, such as cleaning and preparing datasets, creating data visualizations, and running exploratory data analysis using Python libraries like pandas and matplotlib. You'll likely support senior analysts by automating data collection processes and helping to generate regular reports. Collaboration with team members from different departments is common, as you'll need to understand business needs and present your findings in a clear, actionable way. These experiences provide valuable exposure to real-world data challenges and can help you develop both technical and communication skills crucial for advancing in data analytics.

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

To thrive as an Intern Python Data Analyst, you need a solid understanding of data analysis concepts, proficiency in Python, and familiarity with statistics, typically supported by coursework in data science or a related field. Experience using tools like pandas, NumPy, Jupyter Notebook, and SQL, as well as exposure to data visualization libraries such as matplotlib or seaborn, is highly beneficial. Curiosity, attention to detail, and strong problem-solving and communication skills help you extract insights and present findings effectively. These skills are important for accurately analyzing data, translating results into actionable insights, and supporting data-driven decisions within an organization.
What are the most commonly searched types of Python Data Analyst jobs in Pennsylvania? The most popular types of Python Data Analyst jobs in Pennsylvania are:

Junior Data Analyst

Silvi Concrete Products, Inc.

Fairless Hills, PA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Overview
Title of Position: Junior Data Analyst
Location: Fairless Hills, PA (Fully On-Site)
Industry Leading Benefits: Medical, Prescription, Dental, Vision, 401K, Pension, Short- and Long-Term Disability, Life Insurance, Tuition Reimbursement.
Silvi Materials has been expanding our "A" Team of employees since 1947! Our team has grown to 15+ companies, employing over 950 people across 30+ locations in Southeastern Pennsylvania, New Jersey, and North Carolina. Silvi is large enough to provide the stability you need, but small enough that you can feel your individual contribution to our success. We value the fresh ideas and perspectives of each new member of our team.
What does Silvi Materials offer you, you may ask?
  • Phenomenal Benefits: Medical, Vision, Dental, Prescription, Vacation, Paid Holidays, and so much more!
  • Your future in mind: With 401(k) (at select locations) and/or pension options. We want all employees to build a great retirement!
  • Growth at Silvi Materials: We offer each employee the opportunity to move into any facet of our complex business. And our tuition reimbursement program is the perfect springboard to help you get there!

So, what does a Junior Data Analyst do?
A Junior Data Analyst extracts, migrates, cleanses, and organizes raw data to ensure accuracy for business intelligence needs. Key responsibilities include data querying, validation, database maintenance, and dashboards development to support team insights.
Key Responsibilities
  • Data Cleaning and Transformation: Clean, interpret, organize, and validate data to ensure accuracy and consistency multiple sources.
  • Database Management: Utilize tools such as SQL and/or Python to query, extract, and maintain databases.
  • Quality Assurance: Identify and resolve data inconsistencies or missing information. Communicate data validation activities, monitor data quality, and coordinate remediation plans to maintain the accuracy of integrated data.
  • Reporting and Visualization: Conduct data analyses using statistical techniques and data visualization tools. Identify patterns, trends, and correlations in datasets. Create and update dashboards, charts, and reports to communicate findings.
  • Documentation: Develop detailed documentation of data processes/flows, decisions, and configurations to meet compliance and training requirements.
  • Collaboration: Partner with technical and functional stakeholders to align data activities with business objectives.
  • Manage deliverables in accordance with project plans.
  • Contribute to the development and review of Standard Operating Procedures (SOPs), ensuring data practices adhere to organizational standards and requirements.
  • Effectively collaborate with stakeholders by translating technical terminology and processes; support drive data driven decision making.
  • Contribute to the development of a complete data lake and/or data warehouse solution.
  • Support the continuous improvement of data quality and data management processes.

Qualifications & Experience
  • Education: Bachelor's degree in Information Systems, Computer Science, Mathematics, Statistics, Business Administration, Engineering or a related field is required.
  • Technical Proficiency:Proficiency in SQL and Excel is required, with experience in Python or R preferredKnowledge of InterBase scripting is a plus.
  • Analytical Skills:Ability to troubleshoot complex software issues and analyze data to guide decision-making.
  • Understanding of visualization tools such as Power BI.
  • Experience supporting complex system implementations or upgrades is a plus.
  • Ability to collect, organize, and analyze large datasets is a plus.
  • Excellent problem-solving abilities, time management skills, and attention to detail.
  • Experience with ITSM systems like DevOps or Jira is a plus.
  • Experience with data warehouses and/or data lakes is a plus.
  • Knowledge and use of the Microsoft Office Suite is required.
  • Ability to effectively manage multiple priorities in a dynamic environment.

Physical Demands
In a typical work setting, people in this job:
  • Use hands/fingers to type and move office objects
  • Sit for long periods of time
  • Hear sounds and recognize the difference between them
  • See details of objects that are less than a few feet away and far distances
  • See differences between colors, shades, and brightness.
  • Lift 20 pounds on occasion
  • Kneel, stoop, crouch, bend, stretch, twist or crawl, on occasion

Silvi Materials does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor