Data Scientist

Cherry Ventures is supporting our portfolio with this hire

Berlin based - m/f/d - full-time

What we do at Plato

Plato is building the digital backbone of the global trade economy. Starting with the $48T wholesale industry, we empower the modern wholesaler to connect their people and data in a single analytics and workflow hub. By leveraging data science and AI, we automate workflows and combat labor shortages, making SMB wholesalers competitive with large corporations.

🎯 Why we do what we do

The future of wholesale is data-driven. Unlike popular opinion, Industrial SMEs are ready to make the step to become more proactive in their processes but lack the technology to steer them to success. Our founders come from a wholesale family and gathered a rock star team of ex-Big Tech, VC, and top-tier consulting companies to reshape the operations of this $48tn industry. Our initial product leverages cutting-edge data science to provide customized demand forecasts and product recommendations combined with intelligent workflow automation.

We are about to create category-defining software. Our primary customers are C-suite executives within large-scale wholesale and distribution businesses. We are committed to helping them enhance their decision-making processes and optimize their operations through the smart use of their data - bringing their operations into the 21st century! But don’t just hear it from us! We are supported by a list of top-tier EU & US VCs, advisors, and angels providing insights from some of the best SME tech companies such as Miro, Celonis, Personio, Workday, Forto, and Microsoft.

🔮 What we’re looking for

As a Data Scientist at Plato you will be tackling the complex challenge of building versatile models that serve multiple industries, ranging from construction and steel to technical and HVAC wholesalers. Each industry presents unique data sets and requires a tailored approach.

You will have the opportunity to develop a variety of models, such as recommendation engines, dynamic pricing systems, churn prediction models, and customer segmentation algorithms. You will be responsible for the entire lifecycle of these models, from creation to deployment, and ensuring they scale across different industries.

Our platform generates a wealth of data from user interactions, and a key part of your role will be feeding this data back into the models to continuously improve their performance. You’ll collaborate closely with our data engineering and product teams to ensure our portfolio of data products provide value to our users.

🚀 What you’d be working on

• Develop, test, and deploy a wide range of machine learning models, including recommendation systems, dynamic pricing models, churn prediction algorithms, and customer categorisation systems.
• Tackle the challenge of building adaptable models that can be customized across various industries, such as construction, technical, and HVAC wholesale, ensuring that industry-specific needs are met.
• Continuously refine and update models based on real-time platform data and customer feedback to ensure they evolve with our users’ needs.
• Collaborate with data engineers and ML engineers to build efficient data pipelines that feed into and optimise machine learning models.
• Recommendations System knowledge
• Design experiments to assess model performance and iteratively improve accuracy and scalability.
• Implement automated model retraining and monitoring systems to ensure that models remain relevant and continue to perform in production environments.
• Work closely with the product and engineering teams to align model outputs with business goals and deliver actionable insights to customers.
• Build processes to efficiently manage the lifecycle of machine learning models, including versioning, experimentation, and reproducibility across different deployments.

🏅 What you bring along

• 3+ years of experience in data science, with a strong emphasis on machine learning model development and deployment.
• Hands-on experience with recommender systems is highly valued—this will be a core component of the role.
• A strong generalist mindset, capable of owning the full product lifecycle—from translating business problems into data science solutions to building and maintaining models in production.
• Experience in building and running machine learning models end-to-end; you will own your models, ensuring they run smoothly in production and are continuously optimised.
• Experience with MLFlow for model tracking and lifecycle management is desirable.
• Hands-on experience with data engineering tools and platforms; a background in Databricks is highly valued.
• Familiarity with NLP techniques is a plus, especially for customer segmentation and categorisation tasks.
• Ability to wear multiple hats and thrive in a startup environment where flexibility and initiative are key.
• Proficiency in German is plus.
• Based in Germany/EU: We are unfortunately not able to sponsor visas - for this role, you will need to possess an existing EU/German work permit.

🛠️ The tools you will be using

• Python
• PySpark
• Databricks
• MLFlow
• Model Serving Technologies
• CI/CD Tools (e.g., Jenkins, Git)
• Cloud Platforms (AWS)
• Data Engineering Tools (Apache Spark, DBT)

🗒 Hiring Process

Step 1: Intro call (30 min.) - Oliver

• Intro call with one of the founders to get to know each other and introduce Plato.

Step 2: System design call - Oliver + Nikolai

• Technical interview with Nikolai, Backend Lead

Step 3: Technical fit - in office

• 2 technical 1 hour long interviews

Step 4: Meet the founders

• Meet the other co-founders

Step 5: Reference checks

• Before sending the offer, we ask you to provide 2-3 contacts for us to do some reference checks.

Step 6: Offer

• Congratulations! We are convinced by your skills and personality and see a great fit! You will get an offer from us including an appropriate share package.

We are moving fast, and we also want to grow our team fast – that is why we are trying to conclude the whole process within a short time (2-4 weeks).

🖌️ Our way of working

• Office: We work from our beautiful and centrally-located Berlin office
  • We believe working on-site is crucial in our stage to foster ideas and communication
  • We are, however, open to remote work once a year to escape the Berlin winter
• Team: Regular team events and lunches
• Tech: Top of the range tech setup
• Package: Competitive comp and meaningful equity in rapidly growing startup

🦄 You should join Plato if,

• you’d like to be part of a rocket ship backed by top-tier investors from day one,
• digitize an old economy with cutting-edge AI technology,
• while enjoying the adventurous and demanding road of venture building,
• in a team of motivated A-players who push hard to make this a reality

🎯 Our Values

• We go the extra mile to leave a dent.

  1. Hustle: We work hard to make our vision become reality.
  2. Purpose: We are here to enjoy the ride and raise the bar.
  3. Resilience: We persevere during challenges and stay optimistic. 

• We are drivers, not the passengers.

  1. Ownership: We are results-oriented and take end-to-end responsibility.
  2. Proactivity: We initiate new ideas and don’t stay idle.
  3. Velocity: We prioritise action over processes and processes over chaos.

• We are obsessed with our customer.

  1. Empathy: We care about our customers and prioritise their needs.
  2. Reliability: We underpromise and overdeliver on customer needs.
  3. Humility: We understand the problem before we seek solutions.

• We shoot for the moon no matter if we fail.
  1. Boldness: We dare to push the boundaries of what is possible.
  2. Agility: We think critically and quickly adjust to changing circumstances.
  3. Growth: We stay curious and learn from our mistakes. </aside>

• We count on everybody's voice.

  1. Respect: We act with empathy, encourage new ideas and keep a low ego.
  2. Transparency: We adopt an honest, direct yet polite communication style.
  3. Trust: We assume every team member acts with best intentions.

Cherry Ventures is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.