Job description

We are hiring a Data Scientist to support our operations and product teams and take our model development and implementation to the next level in order to derive the right insights and decisions from our diverse and complex data landscape. Within the Global Operations and Analytics Technology team, you will work closely with our stakeholders to build and maintain machine learning models, optimization models, and other tools that improve the HelloFresh customer offering and enhance efficiency of our Operations. Our vision is to develop, implement and maintain best-in-class automated data products that support our growing Supply Chain, in delivering the perfect product, at the right time, to the doorstep of all our customers. We are looking for someone who connects stakeholders to data through key projects, while simultaneously focusing on mentorship and developing internal talent. You will ... • Build complex machine learning development projects • Design and Maintain Statistical and Machine Learning Models in order to enhance our customers experience and operational efficiency • Work closely with our stakeholders to explain complex concepts and advocate for sophisticated analytics • Collaborate with diverse functions across Operations: product, culinary, procurement, fulfillment, logistics and customer care You are... • A skilled Data Scientist with true subject matter expertise in the space • Have a grasp of advanced statistical and machine learning concepts (e.g., Predictive modeling, Clustering, Deep Learning, Time series, Bayesian statistics, NLP, Sampling, etc) • Fluency in Python (required); proficiency using SQL (required); experience with Spark (desired) • An active, solution-oriented member of autonomous, cross-functional agile teams collaborating with business users, product managers, other data scientists, and data analysts • Able to develop an in-depth understanding of HelloFresh's core product and operations, and act as a thought leader for state of the art model development methods and industry best practices • Comfortable operating in fast-paced, dynamic environments and working autonomously • Intellectually curious; don't mind questioning and challenging the status quo • A team player who efficiently collaborates with peers and stakeholders You have... • Bachelor's degree in data science, computer science, statistics, engineering or a related field • 2+ years' experience building and deploying Machine Learning / Statistical Models • Solid grasp of advanced statistical and machine learning concepts (e.g., Predictive modeling, Clustering, Deep Learning, Time series, Bayesian statistics, NLP) • Fluency in Python (required); proficiency using SQL (required); experience with Spark (desired) • Strong analytical and problem-solving skills. • Ability to communicate complex analyses to both technical and non-technical stakeholders, including senior leadership • Experience working with cloud solutions such as Databricks, AWS, Azure • Familiarity with Devops, Model deployment, and CI/CD is a plus You'll get... • Competitive salary, 401k with company match that vests immediately upon participation, and company equity plan based on role • Generous PTO, including sabbatical, and parental leave of up to 16 weeks • Comprehensive health and wellness benefits with options at $0 monthly, effective first day of employment • Tuition reimbursement for continuing education • Up to 75% discount on subscriptions to HelloFresh meal plans (HelloFresh, Green Chef, Everyplate, and Factor_) • Access to 7 different Employee Resource Groups (ERGs) including those for BIPOC, women, veterans, parents, and LGBTQ+ • Inclusive, collaborative, and dynamic work environment within a fast-paced, mission-driven company that is disrupting the traditional food supply chain This job description is intended to provide a general overview of the responsibilities. However, the Company reserves the right to adjust, modify, or reassign work tasks and responsibilities as needed to meet changing business needs, operational requirements, or other factors.

Requirements