Kickfurther is creating a marketplace that serves users who want to earn money by participating in the retail economy, and consumer product businesses who need financing for inventory to meet their own growing demand and production cycles. We use 3rd-party data integrations from a wide variety of sources to vet co-op applications and automate business processes. We regularly close crowd-sourced funding campaigns in just a few minutes as our user base rushes to fund co-ops, meaning that we simultaneously process many transactions in a seamless way.
Kickfurther just closed its largest investment round; there is a lot to accomplish and we have the means to accomplish it. Do you want to join our funded, growing team to help build our differentiated approach focused on crowd-funding physical inventory?
The team is still fairly small, so all your contributions will be noticed. All of your work will be deployed once it is reviewed; you’ll be a key part of building our data platform.
Along with honesty and a strong work ethic, we value the ability to learn and grow, both as individuals and as members of a team. We embrace modern technology, but we also recognize the value of the tried and true so that we can create a robust, stable fintech platform. We stick to lightweight processes and tools, but we place a higher value on the people and the team. We try to create an environment where people are happy, because happy people make better decisions, write better code, and make great products. We prefer simple solutions to complex problems, and complicate things only when absolutely necessary.
In this role, you will need to be proactive, resourceful, persuasive when necessary, and be a team player since you will be working with multiple groups. Your key responsibilities will include:
- 3 - 5 years of data science experience
- Creating data use cases and hypotheses
- Performing various exploratory data analysis
- Stitching various data together in unique ways to create actionable insights
- Helping with the creation of the data science roadmap
- Overseeing and managing the work of junior data scientists
- Creating risk and forecasting models
- Proficiency in Python and Jupyter notebook
- The ability to clean and parse the data to perform analysis and modeling
- Experience working with Pandas, Numpy and Sklearn
- Good knowledge of standard machine learning models in supervised and unsupervised learning
- The ability to pick up new tools and frameworks quickly
- Knowledge and experience in financial modeling/analysis is a plus
- Knowledge of Data Engineering
- Knowledge of creating APIs
- Experience building machine learning models and then deploying them to production
- Strong communication skills – written and verbal
- Competitive salary, based on location
- Health, dental & vision insurance for US-based employees; some cash compensation for non-US
- Paid holidays and vacations
- Work from (almost) anywhere
- Flexible work hours, excellent work/life balance
Contact samir@kickfurther.com