Product Data Science Lead
We are Apheris, a deep tech company at the forefront of the AI revolution that is on a mission to fundamentally reinvent how organizations collaborate and extract value from data.
The Apheris Platform sets out to empower organizations to securely analyze distributed data of multiple parties, while keeping proprietary information private. Our platform allows multiple organizations with complementary data to create an Apheris Data Ecosystem and generate shared value from their data. We have set up such Data Ecosystems for large enterprise customers in healthcare, pharma and chemical R&D, and we are ready for the next big challenges.
Our company is a community of interdisciplinary and industry-leading researchers and engineers. As a team, we work to solve complex problems in order to revolutionize the ways that our customers can interact with data. We are driven by our high-impact values and strive for the impossible. Together, we aim to create a whole that is far more than the sum of its parts. We take pride in Apheris’ supportive environment and share responsibilities and ownership. We are proactive thinkers, are hungry to learn and stay humble as we grow.
We are backed by top investors and tech industry innovators, including LocalGlobe, MuleSoft founder Ross Mason and Twitter board chairman Patrick Pichette (former CFO of Google) and we work closely with Fortune 500 customers to develop our globally leading enterprise Apheris Platform for federated and privacy preserving data science. We are experiencing rapid growth and are recruiting for ambitious and adventurous team members to help us build a better future for data.
About the role
As a Product Data Science Lead at Apheris, you are responsible for defining our data science interaction as one cohesive product and service offering for our high-profile large enterprise customers. You are spearheading our experienced team of data scientists, and act as lead data scientist on customer projects that are developed on top of our core Apheris Platform for federated and privacy-preserving computations. With your ability to understand the needs of data scientists, you own the design of the data science interaction in the Apheris product based on your experience and learnings from customer projects and usability studies.
What you will do
- Lead the design and implementation of the user interaction of data scientists with the Apheris product: you will be in charge of creating the world’s most loveable “pandas/keras for remote data”!
- Gain insights about the usability and technical feasibility of data science interfaces through different product discovery activities such as technical prototyping, rapid iterations, usability studies
- Drive impactful data science projects with our customers: interact with customer stakeholders, understand the business problem, translate the business problem into a data science problem, evaluate data science approaches to tackle this problem and drive the project execution
- Be a hands-on contributor to our software product development: participate in agile sprints, planning, code reviews and demos
You should apply if
- Academic degree in a quantitative discipline, e.g., Computer Science, Mathematics, Physics, Statistics, Bioinformatics, Computational Biology/Chemistry, Engineering
- 5+ years of industry working experience
- Experience with data analysis or related field as a Data Scientist, Machine Learning Engineer, Statistician or related role
- Experience with leading customer projects to translate business problems into data science problems and seeing the bigger picture how data science products impact business processes
- Experience in working in product-focused roles, product management, business analysis, software engineering, or data engineering
- Good feel for UX of data science products (both for GUI and Python SDK/Jupyter Notebook product interactions), product thinking and product discovery
- Understanding of ML-Ops and what it means to bring ML into production
- Expert coding skills in Python and typical data science libraries (pandas, Scikit-learn, Keras, …)
- Genuine interest in working with cutting-edge technology in a fast-paced environment and a young start-up
- Based in Berlin (option to work partly remote)
Bonus points if
- Experience with cloud infrastructure and cloud-native application development, including Docker containers, preferably on AWS
- Experience with distributed or federated data processing (e.g., federated machine learning)
- Experience with software engineering and product development in data-driven product companies
- Experience with project management
- Experience with technical leadership
If you do not match 100% of the above requirements, but you think you fit this role, we encourage you to apply anyway. We value the right people and search based on your personality, potential and motivation to learn and grow. Together we can adapt the role in a way that is meant for you!
What we offer you
- Plenty of room to grow personally and professionally and shape your own role
- A fun and diverse team of smart and driven people
- Industry-competitive compensation
- Access to an employee participation program
- Personal budget for conferences, books, trainings and courses
- The right hardware to make you efficient – be it a laptop with Linux, Windows or a MacBook
- Regular team lunches and social events
- Daily fresh fruit, drinks, coffee (and an occasional beer)
- Inspiring office space in the heart of Berlin directly at the river (Paul Lincke Ufer)
- Possibility to work partly remote
Our interview process is split into three phases:
- Initial Screening: If your application matches our requirements, our hiring manager will invite you to an initial video call. In this 45 minutes interview, you will get to know us and the role. Our hiring manager will be interested in your relevant experiences and skills as well as answer any question on the company and the role itself that you may have.
- Deep Dive: Your second video call will be with a domain expert from our team. Our interviewer will assess your skills and knowledge required for the role by asking you about meaningful experiences or your solutions for specific scenarios in line with the role we are staffing.
- Final Interview: Finally, we invite you to our office for two to three hours of interviewing with our founders, talking about our culture and meeting future co-workers on the ground.