Lead Data Scientist (m/f/d)

About the team

At Adsquare, our mission is driven by our core focus:

Passion – Solving complex challenges with great people, tech, and data.
Niche – Location Intelligence for Programmatic Advertisers.

Our core values are integral to everything we do:

• Drive: We turn ambition into action.

• Resilience: We adapt, persevere, and grow stronger.

• No BS: We value honesty, transparency, and clear communication.

• Humble: We choose modesty over vanity and let results speak for themselves.

• Moral Compass: We do the right thing with fairness, integrity, and respect.

We seek candidates who not only bring top-tier technical expertise but also embody these values in every aspect of their work.

Your Mission

As the Lead Data Scientist, you will spearhead the creation and deployment of data science models and data solutions that power our applications and drive business value. You will lead a dedicated team of data scientists, and ML engineers ensuring that projects are executed on time, within budget, and aligned with Adsquare’s strategic goals. You will work closely with our data analytics engineering team to integrate advanced data science solutions into production workflows.

Reporting Structure:

• You will lead one dedicated data scientist in the data solutions squad, that has 6 members.

• You will hire 2 additional data scientists / AI specialists.

What you will do

• Data Science Product Ownership:
  Develop, deploy, and maintain machine learning models and data science solutions using large-scale datasets (including location signals, geographical data, and audience attributes) to generate measurable business impact.

• Team Leadership & Mentorship:
  Lead, mentor, and manage a team of data scientists and other data professionals, fostering an environment of continuous learning, collaboration, and professional growth.

• Model Development & Deployment:
  Oversee the design, building, tuning, and deployment of ML models at scale using cloud technologies. Ensure robust model performance and integration into production environments.

• Research & Innovation:
  Drive R&D initiatives in data science and machine learning, leveraging cutting-edge techniques and modern LLM AI tools (e.g., ChatGPT, Ollama, Claude, Gemini) to enhance everyday productivity and also to develop innovative AI features such as chatbots or specialized agents based on LLMs.

• Data Engineering Integration:
  Take the role of tech lead in / collaborate with cross-functional teams to ensure seamless data flow and quality of ML models. Leverage data pipelines and ML Ops tools to support model development and monitoring.

• Strategic Oversight:
  Implement frameworks for effective data value extraction and continuously refine processes to optimize cost-efficiency and output quality. Hire and train within your team to continuously optimize your team’s performance.

Desired Background

Experience & Technical Expertise:

• Proven Data Science Expertise:
  Extensive hands-on experience as a data scientist with a track record of designing, building, and deploying ML models that drive business value. Strong foundational skills in the areas of linear algebra, cost functions, probability theory, inferential statistics, as well as experiment design.

• Leadership:
  At least 2 years of experience leading a team of data scientists, providing both strategic direction and hands-on guidance.

• Machine Learning & Cloud Technologies:
  Deep experience in designing, building, and tuning ML models at scale, utilizing cloud platforms and tools. Proven ability to operationalize machine learning in production environments.

• Data Analysis & Modeling:
  Strong background in empirical science, social science, data analysis, and data modeling. Expertise in applying statistical methods and building predictive models. Excellent in explorative data analysis, SQL.

• Technical Skills:
  Proficiency in Python and data science libraries (pandas, numpy, scikit-learn, scipy, statsmodels, tensorflow, keras, PyTorch, langchain, streamlit, mlops) along with tools like FastAPI, streamlit, and Jupyter.
  Experience with dbt is a big plus.
  Familiarity with big data technologies and cloud platforms (e.g., AWS Redshift, Snowflake, BigQuery, AWS SageMaker,