She Loves Tech Problem Statement

Recording

She Loves Tech: Problem Statement Sharing Session

She Loves Tech: Problem Statement 1 - Automate Application Screening

First Prize: 6-month paid internship (based in Singapore) for undergraduates, fresh graduates and working adults
Second Prize: She Loves Tech T-shirt

1st place: $350 USD - Microsoft Funded

Develop an automated solution to fact-check data and score profiles to give appropriate recommendations to the screening team to select competition semifinalists.

The She Loves Tech global competition receives up to 4000 applications a year across 100+ countries on our platform. 

The typical steps our team takes to validate an application is as follows:

  1. Check if the startup meets our competition eligibility criteria
  2. We use a combination of the application fields, company website and information provided in the pitch deck to ascertain the company details on the following.
    • Team – How strong is the team and are they suited to grow this startup
    • Market Opportunity / Problem to be solved – Does this product address a problem in a large enough market
    • Innovation – Is the product introducing a new type of product or new way of doing something
    • Business Model – How will the startup generate revenue
    • Scalability – How easy is it to take this solution to another region or market
    • Traction – How much traction has the startup already gotten.
  3. We conduct due diligence to using platforms like Linkedin (https://www.linkedin.com), Crunchbase (https://www.crunchbase.com/), pitchbook or valid news sites like TechinAsia (https://www.techinasia.com/), TechCrunch to verify the company details found in the application is valid to some degree. 
  4. Once validated, we proceed to evaluate and score the startup accordingly (more details provided in the file below).


To facilitate quicker due diligence and screening, we need to build a solution to allow the automation of data fact checking and eligibility requirements to ensure the applicant fits our eligibility criteria. The solution will help lessen the time for the internal team who manually screen and score to get the top 10 candidates per region. 

For our competition, we are specifically seeking startups in the phase of seed funding under US$5M and have a minimum viable technology product beyond the conceptual stage, AND at least ONE of the following gender lens criteria: Founded by a woman, Majority female users, Majority female consumers, Technology positively impacting women. In the reference file below you will find the following to help you out:

  1. Our eligibility criteria and a description of what the criterion means
  2. Our rubrics on how we score the startups. Take note that different metrics have a different weightage to produce the overall score.
  3. Samples rows of the type of columns that you have access to

 

Reference File

Tech Stack: Power Apps, Power BI, Azure SQL DB, Azure AI

She Loves Tech: Problem Statement 2 - Automate Investor-Startup Matching

First Prize: 6-month paid internship (based in Singapore) for undergraduates, fresh graduates and working adults
Second Prize: She Loves Tech T-shirt

1st place: $350 USD - Microsoft Funded

We need a solution to allow the automation of curated matching of startups lists for investors that aligns with their interest and requirements.

Currently our matching is done manually. We match 1 startup with 1 individual based on their industry and/or regions/country and/or company stage matching. We manually introduce them via email and facilitate their meeting online.

For Example (1)

→ Investor A, Company A, Investing in South East Asia, with an interest Healthcare Technology & Medical Technology, investing in Pre-Seed – Seed startups

Matched with

→ Founder B, Startup B, Operating in Malaysia, with product and focus in the Healthcare Technology, Startup B is currently in Seed stage

For Example (2)

→ Investor C, Company C, Investing in Australia, agnostic with industry (meaning they invest in any industry as long as it’s based in the region and are interesting to them), investing in Pre-A- Series B companies.

Matched with

→ Founder D, Startup D, Operating in Australia, with product and focus in Education Technology, Startup D is a Pre-A series company.

Dataset:

https://drive.google.com/drive/folders/case-2-dataset

Tech Stack: Power Apps, Azure SQL DB

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