Join our ambitious team of data scientists using data, ML, and engineering to create impactful solutions for our customers. We are looking for a team player with a passion for experiments, ML-driven personalisation, and innovation. Collaborate with stakeholders to develop data-driven solutions, communicate insights, and drive business value.
The team - who are we:
We are an ambitious team with the shared passion to use data, data science (DS), machine learning (ML) and engineering excellence to make a difference for our customers.
We are a team, not a collection of individuals. We value our diverse backgrounds, our different personalities and strengths & weaknesses. We value trust and passionate debates. We challenge each other and hold each other accountable. We uphold a caring feedback culture to help each other grow, professionally and personally.
We are now seeking a new team member who is excited about using experiments at scale and ML-driven personalisation to create a seamless experience for our users, helping them find the products and content they didn’t even know they were looking for, and drive engagement and business value.
Our new member - who are you
- You are driven by curiosity and are passionate about partnering with a diverse range of business and tech colleagues to deeply understand their customers, uncover new opportunities, advise and support them in design, execution and analysis of experiments, or to develop ML solutions for ML-driven personalisation (e.g., supervised or unsupervised) that drive substantial customer and business impact.
- You will use your expertise in experiment design, data science, causal inference and machine learning to stimulate data-driven innovation. This is an incredibly exciting role with high impact.
- You are, like us, a team player who cares about your team members, about growing professionally and personally, about helping your team mates grow, and about having fun together.
About the role:
As Data Scientist in this role, your responsibilities include
- Close collaboration with diverse group of stakeholders (e.g., business product owners, sales, marketing, design, product management, engineering) to deeply understand their customers' needs and challenges and translate them into data, analytics, data science or ML solutions
- Development and application of forecasting, causal inference, and machine learning approaches to address customer problems and customer demand
- Making sure that all ML standards are followed and collaborate with Platform for MLOps practice.
- Development of proof of concepts to assess impact & feasibility of opportunities and solutions
- Cultivation of data-driven decision-making, applied to business problems as well as to evaluating and tracking model performance and product success
- Communication of results and insights to business stakeholders across levels, and in our tech demos
- Collaboration with other data science teams to ensure we share learnings, enable each other and promote cohesiveness in a large, complex environment.
Skills & experience we are looking for:
- At least 3+ years of experience in data science, machine learning and analytics
- At least 1+ years of experience in building ML products for forecasting and optimisation
- Bachelor's/Master’s degree in Mathematics, Statistics, Data Science / ML or a closely related field
- Strong proficiency in applied DS/ML using Python and SQL
- Solid understanding of Forecasting process and algorithms and causality
- Strong business intuition and ability to easily empathise with customers
- Excellent communication skills (English) and ability to compellingly present analytics topics to non-technical audiences
- Hands-on experience with applied DS / ML and data / results visualisation and communication
- Self-starter and problem-solver with ability to effectively navigate in a highly ambiguous environment
- A plus: Experience in building real-world, impactful ML products
- A plus: Familiarity with production-level DS/ML, software engineering practises and product management.
- A plus: Familiarity with deep learning techniques for forecasting and recommendations.