Skratch Labs makes sports nutrition designed to help you perform better without offending your gut or your taste buds because we use real food starting from scratch.
Skratch Labs is an outdoor company on the cutting edge of athlete nutrition founded by two pro cycling veterans who started mixing performance drinks in paint buckets at McGuckin Hardware
over 12 years ago. Since then we’ve built an amazing following of impassioned athletes in the US and Europe and we’re growing fast.
We believe food and drink are just better when made from scratch. We also believe that no matter where we find ourselves in life it’s never too late to start from scratch. We use our heads and our hearts in everything we do. Our goal is to help people be better. We work together we are real we perform and we are empathetic. If you’re inspired by athletes and our story and you think you’d thrive in an office full of dogs bicycle posters shenanigans hard work and the
occasional lunchtime knockout (basketball) game this could be the place for you.
Skratch Labs is proud to have been on Outside Magazine's list of the Best Places to Work for two years in a row!
The Demand Planner plays a crucial role in optimizing inventory management through precise demand forecasting and strategic planning. Primary responsibilities include analyzing historical sales data managing forecasts and overseeing all demand planning activities for Skratch’s inventory needs of finished goods packaging and raw materials as needed. This role will work crossfunctionally with other team members primarily in Sales and Marketing and will lead the S&OP process.
You are data driven and highly analytical a strong communicator and enjoy collaborating with people across the organization.You like problem solving making things more efficient value the accuracy of your work and can use data to help others make decisions. You have an interest in supplychain and finance generally and would like to build a strong foundation for your career. You are curious open to learning and looking at problems differently.
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