5 Ways to Instantly Add Value as a Data Scientist at a Small Startup
Warning — no machine learning or AI involved!
Imagine this scenario: You’ve been hired as the token data scientist at a small startup to work on a machine learning project. However, as you set out to complete your project, you realize it could be months or even years until your machine learning project is fully integrated into production software. Data science is a broad field, so when you’re the first data hire at a small startup, you’ll want to leverage your data skills across the company to help the company grow while your machine learning contribution comes to fruition. Here are five ways I’ve found to instantly add value when I have slow-downs in moving my machine learning project forward.
- Contribute to the Product
- Create Marketing Content
- Estimate the Product ROI
- Create Data-Driven Processes
- Define and Track KPIs
Contribute to the Product
Given your coding experience, there are likely small contributions you can make to the software product being developed. In my case, this was contributing some of the D3.js code to create visualizations for the analytics dashboard in the software platform. Since my JavaScript coding is limited, I also created mock-ups of the best way for users to visualize the data. Your experience creating simple yet effective data visualizations is definitely an asset at a small start-up.
Create Marketing Content
Generating qualified marketing and sales leads is critical for a small business. My company’s sales strategy is particularly focused on inbound marketing, so creating interesting content is key to our growth. Since I was already accumulating large amounts of data for my machine learning project, I crunched some preliminary numbers to be used for infographics and data visualizations for sales decks and marketing content. Your ability to create meaningful, digestible statistics that catch the eye of potential customers is crucial for the sales and marketing teams.
Estimate the Product ROI
Nearly every B2B startup is going to want some sort of Return on Investment (ROI) estimation to convey the value of the product to potential customers. It’s also very likely that the data to estimate the gain on investment (i.e. monetary benefit from purchasing your product) does not exist, so you’ll need to be creative to calculate a reasonable estimate. This is definitely not a simple task, but who better to draft a plan, gather the data, clean the data, create a model, and crunch the numbers than the data scientist?
Create Data-Driven Processes
Being efficient while still being nimble is a delicate balance at a startup. Keeping that in mind, implementing a few strategic data-driven processes can save a lot of employee time and potentially reduce hiring needs. For a data scientist, this could entail setting up data pipelines to give the customer success team more details about customers, auto-magically combining data sources to give the sales team more insights into their target accounts, or setting up a dashboard for the company’s business analytics. This will likely need some creativity, a deep understanding of internal operations, and buy-in from your coworkers. However, increasing efficiency can have a big positive impact on the company.
Define and Track KPIs
Your ability to help teams brainstorm and track Key Performance Indicators (KPIs) will prove beneficial when assessing how the company is improving over time. For me, this was tracking user KPIs (like figuring out how to measure monthly active users) and tracking KPIs related to business analytics (such as Net Promoter Score (NPS) results). Larger businesses with lots of KPI data are even trying to use metrics to train machine learning models aimed at spurring future growth (I guess I lied in the subtitle, I did mention machine learning).
Working at a small startup often involves wearing many hats. If you’re the team’s data guru, then you’ll likely be incorporating data into various aspects of the company. I personally think this is the best part of working at a startup — the variety of day to day tasks and the creativity required to solve the company’s problems with limited resources. Figuring out how to apply one of the above five projects at your company may be a great way to get started!
