Constructor is the only search and product discovery platform tailor-made for enterprise ecommerce where conversions matter. Constructor's AI-first solutions make it easier for shoppers to discover products they want to buy and for ecommerce teams to deliver highly personalized experiences that drive impressive results. Optimizing specifically for ecommerce metrics like revenue, conversion rate and profit, Constructor generates consistent $10M+ lifts for some of the biggest brands in ecommerce, such as Sephora, Petco, home24, Maxeda Brands, Birkenstock and The Very Group. Constructor is a U.S.-based company that was founded in 2015 by Eli Finkelshteyn and Dan McCormick.
We specialize in developing a cutting-edge search and discovery platform, encompassing search, autocomplete, browse, and recommendations, tailored specifically for online retailers, suppliers, and shops. Our goal is to provide all online stores with the ability to have state-of-the-art product discovery powered by AI that optimizes for the key e-commerce metrics, which differentiates us from our competitors.
Boasting a robust infrastructure, we handle billions of requests daily and manage a vast data ecosystem, including ~400 GB of data intake daily and approximately 2PB stored in our data lake.
Merchant Intelligence Team
- An important part of our product is the customer dashboard that helps merchandizers to analyze shopping behavior and manually adjust algorithmic results. The goal of the Merchant Intelligence team is to:
- Help merchandizers achieve their e-commerce goals, increasing satisfaction with their sites and retention of customers.
- Provide insights to merchants they can't get anywhere else.
- Become a critical point of merchant planning, decision-making, and analysis, so we become a sticky part of their organization.
Challenges You Will Tackle
- Enhance the dashboard experience for merchandizers by building analytics that provide actionable insights to improve e-commerce KPIs.
- Perform data exploration and research user behavior.
- Implement end-to-end data pipelines to support real-time analytics for essential business metrics.
- Take part in product research and development, iterate with prototypes and customer product interviews.
Requirements
- You are proficient in BI tools (both data analysis and building dashboards for engineers and non-technical folks).
- You are keen to not just prepare more data, but to think critically about how that data can deliver valuable insights and drive impactful decisions for non-technical end users.
- You are an excellent communicator with the ability to translate business requests into technical language and vice versa.
- You are excited to leverage massive amounts of data to drive product innovation and deliver business value.
- You are proficient at SQL (any variant) and well-versed in exploratory data analysis with Python (pandas & NumPy, data visualization libraries).
- Practical familiarity with the big data stack (Spark, Hive, Databricks).
- You are adept at fast prototyping and providing analytical support for initiatives in the e-commerce space by identifying and focusing on relevant features and metrics.
- You are willing to develop and maintain effective communication tools to report business performance and inform decision-making at a cross-functional level.
- You get excited to hear feedback from customers and figure out potential solutions.
- You're familiar with math statistics.
Benefits
- Unlimited vacation time — we strongly encourage all of our employees to take at least 3 weeks per year.
- A competitive compensation package, including stock options.
- Company-sponsored US health coverage (100% paid for employee).
- Fully remote team — choose where you live.
- Work from home stipend! We want you to have the resources you need to set up your home office.
- Apple laptops provided for new employees.
- Training and development budget for every employee, refreshed each year.
- Parental leave for qualified employees.
- Work with smart people who will help you grow and make a meaningful impact.
