Mollie is seeking a Data Scientist to join its growing Machine Learning Craft.
Job Description
The successful candidate will be responsible for developing predictive ML models that provide decision intelligence to various domains within Mollie.
They will use machine learning to power Mollie's efforts in lead sourcing and lead scoring, identifying relevant companies and data points online.
The models will be used to enrich leads with relevant data points and prioritize them using predictive machine learning algorithms.
The Data Scientist will spend most of their time developing in Python alongside the team of DSs and MLEs.
They will also interface directly with subject matter experts and stakeholders to evaluate the feasibility of potential DS use cases or explain how their model works during a Team Review.
Key Responsibilities
* Develop and maintain ML models for a range of use cases in the GTM Optimization Domain at Mollie.
* Perform efficient exploratory data analysis (EDA) and present key insights to colleagues & stakeholders.
* Avoid wasting resources on unnecessary tasks and focus on delivering high-quality results.
* Collaborate closely with MLEs to prepare code and models for production using our ML Platform.
* Contribute regularly to our bi-weekly DS Community of Practice (knowledge sharing sessions).
* Understand the commercial objectives of the problem space and use cases, evaluating the feasibility of new use cases for ML in the GTM Optimization Domain.
Requirements
* 1-3 years experience in data science and machine learning, including the development of models that successfully went to production.
* Expertise in applied ML on structured data, particularly regression and classification problems using boosted decision tree (BDT) algorithms.
* Basic experience with Generative AI, especially leveraging GenAI in non-chat applications.
* Approach complex problems in a structured way, always looking for the simplest, pragmatic solutions.
* Understand technical and non-technical constraints of a business problem.
* Detail-oriented but can quickly shift priorities if required.
* Enjoy working collaboratively in a cross-functional and distributed team environment.
* Great presentation skills and ability to communicate to a wide variety of audiences.
* Strong foundation in statistics.
* Solid software engineering skills and love coding in Python.
* Knowledge of Linux shell and Git for version control.
* Proficiency in scikit-learn API.
* Comfortable in an agile Way of Working, with Scrum or similar frameworks.
Nice to Have
* Experience with Google Cloud Platform Vertex AI or similar (e.g. SageMaker).
* Experience in the financial services industry (banking or fintech).
* Familiarity with DevOps & MLOps principles.
* M.Sc. or Ph.D. in Machine Learning, Computer Science, Physics, or similar.
Benefits
Our employees enjoy a range of benefits, including:
* MacBook
* Birthday off
* Complimentary baby days
* 20 days working from abroad
* 22 holiday days
* Work from home budget
* Bike lease plan
* Pension contribution
* Health insurance
* Equity plans
* Referral bonus
* Learning platform
How We Hire
Our hiring process typically consists of three steps:
1. Step 1: Apply - Our Talent Acquisition team and hiring manager review your application and respond within 2 weeks.
2. Step 2: Screening call - If you seem like a Mollie-in-the-making, we invite you to a screening call so we can learn more about each other.
3. Step 3: Are you the one? - You'll have two or more interviews. And if it's a highly technical role, we'll also assess the specific skills you'll need.
Diversity, Equity & Inclusion
At Mollie, we celebrate diversity of people and perspectives, and we're proud to be an equal opportunity employer.
We value our differences because we know that individual perspectives make our products and culture stronger.
So we encourage everyone to be their authentic selves and prioritise respect.
At the end of the day, we are a team of individuals – diverse yet united by our vision to eliminate financial bureaucracy.