Eric S.

Eric S.

Washington DC-Baltimore Area
295 followers 299 connections

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About

Distinguished career in Finance and Accounting, crowned by a pivotal role as a DoD…

Activity

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Experience

  • Take2 Consulting, LLC Graphic

    Take2 Consulting, LLC

    Arlington, Virginia, United States

  • -

    Alexandria, Virginia, United States

  • -

    Sterling, Virginia, United States

  • -

    Washington DC

  • -

    New York

  • -

    Westhampton Beach, NY

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    Hoboken, NJ

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    Eglin Air Force Base, Florida

Education

Licenses & Certifications

Volunteer Experience

  • Junior Achievement of New York Graphic

    Coordinator Of Volunteers

    Junior Achievement of New York

    - 2 months

    Education

  • The Jericho Project Graphic

    Project Coordinator

    The Jericho Project

    - 3 years 4 months

    Social Services

    Veteran's Initiative - Holiday decorating of The Jericho Project Veteran's Home,

  • GrowNYC Graphic

    Volunteer

    GrowNYC

    - Present 5 years 1 month

    Environment

    Veteran's Initiative - Volunteered for GrowNYC and teaming with Bloomberg employees to assist in clean-up and landscaping beautification project

Projects

  • Dynamic Sales Forecasting Dashboard

    1. Data Collection and Cleaning:

    - Gather historical sales data, which includes variables like date, product, region, and sales amount.
    - Use Python's pandas library to clean and preprocess the data, handling missing values, outliers, and ensuring data consistency.

    2. Time Series Analysis:

    - Implement time series forecasting models like ARIMA or Prophet in Python to predict future sales.
    - Split the data into training and testing sets to validate the accuracy of the…

    1. Data Collection and Cleaning:

    - Gather historical sales data, which includes variables like date, product, region, and sales amount.
    - Use Python's pandas library to clean and preprocess the data, handling missing values, outliers, and ensuring data consistency.

    2. Time Series Analysis:

    - Implement time series forecasting models like ARIMA or Prophet in Python to predict future sales.
    - Split the data into training and testing sets to validate the accuracy of the forecasting model.

    3. Excel Integration:

    - Use Python's openpyxl or xlsxwriter libraries to export the processed data and predictions into an Excel workbook.
    - Design a dynamic Excel dashboard using pivot tables, charts, and slicers to showcase the historical sales data and future predictions.

    4. Interactive Features:

    - Implement dropdown lists in Excel to allow users to select specific products or regions.
    - Use Excel's conditional formatting to highlight significant increases or decreases in sales.

    5. Automated Data Refresh:

    - Write a Python script that can be scheduled (e.g., using Task Scheduler) to periodically fetch new sales data, run the forecasting model, and update the Excel dashboard.

    6. Documentation:

    - Create a detailed documentation on the project's methodology, tools used, and insights derived from the analysis.

    Outcome: A fully interactive sales forecasting dashboard in Excel that leverages the power of Python for data analytics. This tool will not only provide insights into past sales performance but also offer valuable predictions for future sales, aiding in business decision-making.

Languages

  • Spanish

    Limited working proficiency

Organizations

  • American Society of Military Comptrollers

    -

    - Present

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