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Sql Python Excel Power Bi Tableau Jobs in Tennessee

Data Scientist

Nashville, TN · On-site

$60K/yr

... SQL, Python (Pandas), and Excel. * Exploratory Data Analysis (EDA) * * Conduct exploratory data ... Develop and maintain interactive dashboards using Tableau, Power BI, or Python (Matplotlib, Seaborn ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

Clean, transform, and analyze large datasets from various sources (Excel, SQL, SharePoint, etc ... Exposure to other data visualization tools (e.g., Tableau) preferred * Experience with Microsoft ...

... Power BI/Tableau). * Very strong communication skills with a proven ability to partner with ... SQL, ETL/ELT, and Python * Understanding of B2B and direct to consumer (DTC) selling models ...

Power BI Consultant

Nashville, TN · On-site

$46.25 - $63.50/hr

Power BI Report Writer - Payroll Analytics Location: On-Site Employment Type: Full-Time Overview ... Experience with SQL or other data query languages. * Familiarity with HRIS data structures ...

Develop and optimize SQL queries, stored procedures, and data transformations * Build and maintain ... Knowledge of BI tools (Power BI, Tableau) * Domain experience in HealthCare * Familiarity with HL7 ...

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Sql Python Excel Power Bi Tableau information

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in SQL and Python for data manipulation, and a solid understanding of Excel for data organization and calculations. Familiarity with data visualization tools like Power BI and Tableau, as well as relevant certifications such as Microsoft Certified: Data Analyst Associate, are highly valuable. Attention to detail, problem-solving abilities, and effective communication skills help translate complex data findings into actionable insights for stakeholders. These skills are crucial for extracting meaningful information from data, driving business decisions, and presenting results clearly to both technical and non-technical audiences.

How do professionals using SQL, Python, Excel, Power BI, and Tableau typically collaborate within data teams?

Professionals skilled in SQL, Python, Excel, Power BI, and Tableau often work closely with data analysts, data engineers, and business stakeholders. They collaborate by gathering requirements, extracting and transforming data (using SQL and Python), and then visualizing insights (with Power BI and Tableau) or conducting ad-hoc analysis in Excel. Regular communication and sharing of dashboards or reports are common, as is peer review of data models and code. This collaborative environment helps ensure accurate, actionable insights for the organization.

What are SQL, Python, Excel, Power BI, and Tableau jobs?

Jobs that require skills in SQL, Python, Excel, Power BI, and Tableau typically involve working with data analysis, data visualization, and business intelligence. Professionals in these roles use SQL to manage and query databases, Python for data processing and automation, Excel for organizing and analyzing data, and Power BI or Tableau to create interactive dashboards and reports. These roles are common in industries like finance, healthcare, marketing, and technology, where data-driven decision-making is essential. Common job titles include Data Analyst, Business Intelligence Analyst, and Data Scientist.

What is the difference between Sql Python Excel Power Bi Tableau vs Data Analyst?

AspectSql Python Excel Power Bi TableauData Analyst
Required SkillsSQL, Python, Excel, Power BI, TableauData analysis, SQL, Excel, visualization tools
Work EnvironmentBusiness intelligence, data visualization, reportingData interpretation, reporting, business insights
Industry UsageTech, finance, marketing, consultingFinance, healthcare, retail, marketing

Sql Python Excel Power Bi Tableau professionals focus on data extraction, analysis, and visualization using specific tools. Data Analysts interpret data to provide insights, often using similar skills but with a broader focus on business decision-making. While both roles require SQL and Excel, the former emphasizes technical data manipulation and visualization tools, whereas Data Analysts focus on understanding data trends and presenting actionable insights.

What are popular job titles related to Sql Python Excel Power Bi Tableau jobs in Tennessee? For Sql Python Excel Power Bi Tableau jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Sql Python Excel Power Bi Tableau jobs in Tennessee look for? The top searched job categories for Sql Python Excel Power Bi Tableau jobs in Tennessee are:
What cities in Tennessee are hiring for Sql Python Excel Power Bi Tableau jobs? Cities in Tennessee with the most Sql Python Excel Power Bi Tableau job openings:

$60K/yr

Full-time

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


Job description

Job Title : Data Scientist
Location : Hermitage, TN
Wage : $60,000
Job Duties :
  1. Data Acquisition, Cleaning & Preprocessing

    • Assist in collecting, validating, and preprocessing structured and unstructured datasets from internal and third-party financial systems.
    • Perform data quality checks, resolve anomalies, and maintain metadata using SQL, Python (Pandas), and Excel.

  1. Exploratory Data Analysis (EDA)

    • Conduct exploratory data analysis to identify trends, outliers, and correlations within financial and operational datasets.
    • Support the preparation of data summaries, distribution checks, and hypothesis validations.

  1. Automation & Data Pipeline Support

    • Assist in developing automation scripts and data pipelines using Python, Excel macros, and RPA tools (e.g., Blue Prism) to streamline data ingestion and transformation.
    • Support version control and CI/CD practices using Git repositories.

  1. Predictive Modeling & Forecasting

    • Support senior data scientists in building and validating statistical and machine learning models to forecast revenue trends, customer churn, or financial health.
    • Participate in refining time-series models and basic regressions using Python (Scikit-learn, StatsModels).

  1. Financial & Business Analysis

    • Contribute to financial modeling by evaluating key metrics (e.g., EBITDA, revenue growth, margins) and integrating external macroeconomic indicators into models.
    • Work alongside business analysts to align technical models with stakeholder requirements.

  1. Data Visualization & Dashboarding

    • Develop and maintain interactive dashboards using Tableau, Power BI, or Python (Matplotlib, Seaborn) to communicate insights to internal stakeholders.
    • Automate reporting templates and visualization tools for monthly and quarterly updates.

  1. Documentation & Compliance

    • Maintain comprehensive documentation for model assumptions, workflows, data dictionaries, and QA protocols.
    • Ensure data practices align with internal governance policies and industry regulations (e.g., GDPR, SOX).

  1. Collaboration & Communication

    • Work closely with cross-functional teams including finance, data engineering, and business strategy teams to align analytical efforts with organizational goals.
    • Participate in sprint meetings and contribute to shared knowledge repositories.

  1. Model Monitoring & Feedback Loops

    • Assist in tracking model performance and accuracy post-deployment using standard KPIs (e.g., RMSE, MAE).
    • Help integrate user feedback and error analysis into model retraining cycles.

  1. Professional Development

    • Attend internal workshops and training sessions on data science tools and methodologies.
    • Stay informed of advancements in machine learning, financial modeling, and analytics platforms.