You are driven and passionate about extracting value from data and about building highly automatic and scalable data solutions and data transformation pipelines
You strive for excellence and high-value output and at the same time remain humble, grounded and approachable
You are resilient and thrive in complex situations where you need to handle many requests and acceptance criteria
You communicate regularly, clearly, concisely and openly in the interest of problem solving in a team
For all your projects you do thorough research and back up all your ideas with data. You always lead by example
You are guided by a moral compass knowing to do the right thing following the principles of excellent and fair leadership, following the scientific method and always thriving to deliver excellent products, in a cost-efficient manner, bringing maximum value to Adsquare’s customers
You have a Master's Degree or PhD in a relevant quantitative empirical science field (e.g. Social Sciences, Psychology, Neuroscience, Physics, Statistics, Machine Learning, Mathematics, Computer Science, Economics) or equivalent practical experience
You have ample experience in leading and mentoring a technical team, providing both strategic direction and hands-on guidance
You have excellent communication and organizational skills, with the ability to convey complex technical information clearly and effectively
You are fluent in English; Knowing German or another European language is an advantage
You have a proactive approach to problem-solving, an aptitude for promoting data literacy across the organization and you love learning new things, expanding your skills and also empowering your team to learn and grow continuously
You have multi-year experience in working and leading teams according to software engineering principles (agile, 12-factor app, software design)
You have strong proficiency in Python, with knowledge of key libraries such as pandas and numpy, FastAPI, streamlit, jupyter, scipy, statsmodels, scikit-learn, pytest, poetry, dask, PySpark etc.
You have a solid foundation in computer science principles, including data structures and algorithms, with a focus on data analytics engineering, databases, data analysis, descriptive statistics, ideally also on inferential statistics and probability theory
You have experience in handling and processing very large datasets (100s of GBs to many TB), particularly tabular, geo-spatial and behavioral data
You have proven hands-on experience with dbt, SQL, databases as well as Tableau (or similar BI tools); Airflow and docker experience is highly valued
You have experience with working with big data warehouses and technologies, such as Athena, Iceberg, DataBricks, PySpark, Redshift, Snowflake, BigQuery in conjunction with dbt
You are familiar with the AWS stack (Glue, Athena, Redshift, Lambda, Batch, StepFunctions)
You ideally have deployed infrastructure with Terraform and have used Kubernetes regularly in your projects
You ideally have some data science experience in choosing and implementing machine learning algorithms
You ideally have empirical scientific experience, having designed and conducted scientific experimental research