INCRMNTAL is searching for the Head of Data Science out there!
We are a 4 years old startup founded by successful serial entrepreneurs and a strong team with the vision to evolve digital marketing from the measurement of traffic to measuring VALUE.
Advertising for the past 100+ years has faced a strange dilemma: “Half the budget I spend on Advertising is wasted. The problem is – I don’t know which half” (John Wanamaker, 1838-1922)
We are a deep machine learning and AI company, using the latest technologies, to solve a really simple question – “which half is wasted?”
INCRMNTAL launched in summer of 2020, backed by strategic investors from around the world who believe in what we’re doing.
We have customers and a constant flow of interest from the press, investors and more large companies who want to join us.
Job Summary:
The Head of Data Science will be responsible for shaping and executing the company’s data science strategy. This role requires a combination of technical expertise, leadership skills, and business acumen. The ideal candidate will lead a team of data scientists and collaborate with cross-functional teams to solve complex business problems, drive innovation, and create actionable insights from data.
Role Description:
As the Head of Data Science your role will be to:
- Lead the Data Science team and the whole Data Science activities of the company providing guidance, mentorship, and support.
- Oversee the planning, execution, and delivery of data science projects.
- Prioritize and allocate resources to ensure timely and successful project completion.
- Report to the Co-Founder & CTO and collaborate with different head of departments (Product, Business operations, sales etc.) to leverage data insights for strategic decision-making.
- Develop and implement data strategies that align with the company's goals.
- Use analytical, statistical and technical skills to understand large, complex datasets with the aim to eliminate waste and measure incrementality for advertisers.
- Lead, Develop & improve algorithms for automated decision making around causality, and budget planning
Determine, analyze, maintain, and report on core marketing metrics to identify causal relationships between marketing actions and outcomes. - Translate data into actions and recommendations – appropriately interpreting and building on findings, and fully exploiting insights
Key Requirements:
- Proven experience in a senior data science management role.
- Min. 8 years of work experience in a Data Science role – experience in SaaS, B2B and/or data-heavy products would be ideal
- Excellent leadership, communication, and project management skills.
- Ability to work collaboratively with cross-functional teams and influence decision-making.
- Strong problem-solving skills and a results-oriented mindset.
- Strong statistical and research skills with a track record of using a variety of math and statistical methods (especially Causal
- Inference, Prediction models, Bayesian Method)
- Excellent development skills (Python required, R or Scala a plus)
- Experience in working on big data with distributed computing (Spark, Airflow, Kubernetes)
- Familiarity with digital marketing, advertising or analytics is a plus
- Extensive experience in the Time Series domain, working with small and large time series frames
- MS.c or PHD in Mathematics/ Computer Science/ Statistics/ Physics.
Benefits of Joining INCRMNTAL:
- We are a new startup with a LOT of supporters and positive attention from investors, press and customers. Joining early means that you could be part of our success.
- You will be granted share options as an early employee.
- We are passionate, solution-oriented people who are accountable to our actions.
- At INCRMNTAL, you should be ready to make decisions yourself. We say: “Don’t ask for permission –beg for forgiveness ☺”.
- We care and respect one another, as we are ALL people – our titles define our roles and responsibilities, they do not differentiate us.
We are accepting applications regardless of any external factors. Everyone is welcome to apply.