Data Scientist at Sterling Bank

We're looking for a Data Scientist excited to help *build the best digital banking products.* You'll have the opportunity to super charge our user growth to help shape the future of what we build. You will enjoy working alongside brilliant engineers and product managers, with the opportunity to see your insights turned into real products on a regular basis.

# About this Role

Our Data Science team's mission is to

> Enable us to Make Better Decisions, Faster

This mission encompasses three major areas of work:

1. product analytics, to help teams understand our customers and improve our app
2. domain analytics, to support teams who are working in specific banking disciplines (e.g., lending, operations, finance, and financial crime), and
3. machine learning, where we design and build system that automate decisions across products.

While we take a flexible approach and frequently help each other across these areas, we each have one domain as our primary focus. We work in cross-functional squads, so every data scientist is a member of the central data team as well as fully embedded into another team alongside engineers, designers, product managers etc.

As part of your role, you'll:

• Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with our products and how those insights can inform our product strategy
• Monitor key product metrics, understanding root causes of changes in metrics
• Guide and enable product teams to measure things that matter; initiate or help run A/B experiments to keep improving everything we do
• Drive together with the finance team a unified company-wide understanding of the lifetime value of our users and how different product features are impacting user profitability
• Liaise with engineers to keep making sure we collect the right data to produce relevant business insights

You should apply if:

• You're impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well
• You're commercially minded and can put numbers into business perspective
• You are focused on results and have demonstrated success in using analytics to drive the understanding, growth, and success of a product.
• You’re as comfortable getting hands-on as taking a step back and thinking strategically
• You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• You're a team player whom your colleagues can rely on
• You have solid grounding in a scripting language (e.g. Python, Perl)

# **Qualifications & Characteristics**

As an ideal candidate for this role, you would have:

• At least **2 years** of professional experience doing quantitative analysis for product or growth analytics,*preferably in a *fast moving tech company*
• Experience in conducting large scale A/B experiments in the past
• A solid understanding of statistics (e.g. hypothesis testing, regressions)
• The ability to *communicate* the results of analyses with the rest of your team to influence the future strategy of the product and business
• Experience manipulating data sets through statistical software (ex. R, SAS, pandas) or other methods
• Experience automating analyses and authoring pipelines via MongoDB and python based ETL frameworks

Logistics

Our main office is in Marina Lagos, though you have the opportunity to work remotely twice a week.

# What the hiring process looks like... typically

• an on-site interview (varies by role and seniority, but we may invite you to a technical interview, product/design-centric session, and possibly an engineering leadership interview).
• a short meeting with our head of engineering.

You'll be given an offer if you can pass these two stages.

We understand that everyone's situation is different, that you may be able to dedicate more or less time to our hiring process, or have other restrictions. If any of our process is challenging for you and you'd like us to offer alternative or special arrangements, *please* let us know. We're committed to finding the right people, and don't want anyone to be excluded because of their circumstances.