Laura Klipp

Laura Klipp

Santa Clara, California, United States
1K followers 500+ connections

About

I pride myself on being a data MacGyver and emphasizing time-saving automation in my…

Activity

1K followers

See all activities

Experience

  • Google Graphic

    Google

    San Francisco Bay Area

  • -

  • -

    Oakland, California, United States

  • -

    Oakland, California, United States

  • -

    Palo Alto, California, United States

  • -

    Palo Alto

  • -

    San Francisco Bay Area

  • -

    San Francisco Bay Area

  • -

    London, United Kingdom

  • -

    Boston, MA

Education

  • Santa Clara University Leavey School of Business Graphic

    Santa Clara University Leavey School of Business

    -

    -

    Activities and Societies: President of Business Analytics and Data Science Association

    Pursuing higher education in the field of data analytics in order to gain a technical skill set while also engaging in highly creative problem-solving and business strategy.

  • -

    -

Courses

  • Data Science with Python

    -

  • Data Visualization with Tableau

    -

  • Database Management Systems (SQL)

    -

  • Deep Learning

    -

  • Econometrics with R

    -

  • Internet Marketing and Ecommerce

    -

  • Machine Learning with Python and R

    -

  • Marketing Analytics

    -

  • Optimal Pricing Analytics and Strategy

    -

  • Time Series

    -

Projects

  • Retail Returns Analysis

    -

    Analyzed multiple data sets from Zale's to determine the impact of a return policy change on the company’s revenue and profits using multiple regression models and machine learning to impute missing data.

  • Doctor Reviews Text Analytics

    -

    Scraped two prominent doctor review websites, to collect patient reviews for doctors across 6 specialties in 5 cities around the United States. Implementing word frequency analysis, and Fisher's Discriminant Scores, we were able to identify the most frequent and discriminating words between good and bad reviews. Using WordtoVec and LDA, we were then able to find the most important topics that were either in good or bad reviews, helping us to understand the context behind the most common words…

    Scraped two prominent doctor review websites, to collect patient reviews for doctors across 6 specialties in 5 cities around the United States. Implementing word frequency analysis, and Fisher's Discriminant Scores, we were able to identify the most frequent and discriminating words between good and bad reviews. Using WordtoVec and LDA, we were then able to find the most important topics that were either in good or bad reviews, helping us to understand the context behind the most common words appearing under each category of reviews.

    Other creators
    See project
  • FlyEx - Facebook Marketing Analysis

    -

    Using data preparation techniques in Python and multiple regression techniques in R, we quantified the effect of customer discounts and Facebook campaigns on flight bookings and revenue. From the analysis, we presented a future campaign strategy to executive leadership based on the most responsive customer segments based on geographic and demographic data.

    Other creators

Recommendations received

View Laura’s full profile

  • See who you know in common
  • Get introduced
  • Contact Laura directly
Join to view full profile

Other similar profiles

Explore top content on LinkedIn

Find curated posts and insights for relevant topics all in one place.

View top content

Add new skills with these courses