Kinesso brings together the best minds in data, technology and media activation to deliver seamless data-driven marketing solutions. As a technology-enabler, Kinesso powers marketing systems through a proprietary suite of applications that integrate ad tech and martech. Kinesso’s application framework spans audience, planning, and activation, delivering insights and business outcomes for leading global brands.
We are looking for a Data Scientist to create technology solutions for IPG’s Interact platform, specializing in the application of ML and AI to automate machine-assisted audience creation.
The ideal candidate has hands-on experience implementing solutions in a modern architecture stack and enjoys working in a startup-like environment, both independently and with cross-functional teams.
Responsibilities
Execute the Strategy:
- Collaborate with a global team of data scientists, engineers, and product managers to deliver audience creation products to hundreds of users.
- Apply AI, ML, and optimization algorithms to audience creation, segmentation and insights. Productionize processes for use in Interact, Kinesso and Interpublic Group (IPG)'s integrated platform that brings together data, media, creative, and production for a streamlined approach to brand marketing.
- Build data science with engineering toolkits for job orchestration, MLOps, CI/CD, RESTful APIs, Snowflake stored procedures and scalable infrastructure.
- Scale data science across our agencies’ client portfolio. Data science should be simple, easy-to-explain, and anchored in business value.
Innovation and Development:
- Push the boundaries of machine-assisted human decisioning, for example, AI led methodologies to discover the best variables available in our Snowflake data lake.
- Foster a culture of innovation, encouraging the exploration of new techniques and technologies that enhance and scale our product capabilities.
Collaboration and Communication:
- Move in lockstep with team members across Data Science, Product, and Engineering, ensuring clear and effective communication of product roadmaps, statuses, challenges, and successes.
- Collaborate closely with product teams to understand their needs and integrate AI/ML technologies into our products that meet those needs, driving value and efficiency.
IPG Mediabrands is the media and marketing solutions division of Interpublic Group (NYSE: IPG). IPG Mediabrands manages over $47 billion in marketing investment globally on behalf of its clients across its full-service agency networks UM, Initiative and Mediahub and through its award-winning specialty business units Healix, Kinesso, MAGNA, Mediabrands Content Studio, Orion Holdings, Rapport, and the IPG Media Lab. IPG Mediabrands clients include many of the world’s most recognizable and iconic brands from a broad portfolio of industry sectors including automotive, personal finance, consumer product goods (CPG), pharma, health and wellness, entertainment, financial services, energy, toys and gaming, direct to consumer and e-commerce, retail, hospitality, food and beverage, fashion and beauty. The company employs more than 18,000 diverse marketing communication professionals in more than 130 countries. Learn more at www.ipgmediabrands.com.
We are looking for a Data Scientist to create technology solutions for IPG’s Interact platform, specializing in the application of ML and AI to automate machine-assisted audience creation. The ideal candidate has hands-on experience implementing solutions in a modern architecture stack and enjoys working in a startup-like environment, both independently and with cross-functional teams.
Experience and Qualifications
Key technical skills:
- Python: Advanced knowledge of Python is essential (Numpy, Pandas,…), with the ability to write efficient, clean, and commented code for model and package development, automation processes and application development.
- Machine Learning: Expertise in machine learning, including regression, classification, and ensemble methods like Logistic Regression, Random Forest and Gradient Boosting. Skilled in model development and feature engineering.
- AI: Experience working with LLMs, sentence transformer models, vector embeddings, RAG, semantic search (Gemini, Hugging Face, LangChain). Familiarity with coding assistants like GitHub Copilot or Cursor is desirable.
- Data Management: Proficient in data manipulation and transformation techniques. Experience with SQL databases, ETL processes and frameworks (Dagster, Airflow, dbt,…), and data modeling as well as cloud-based data warehousing solutions like Snowflake or Google BigQuery. Understanding of data governance and quality control.
- MLOps: Experience in overseeing the life cycle of machine learning models from development to production. This includes observability, reproducibility and evaluation of both data and models.
- CI/CD: Experience with agile development methodologies, such as Scrum or Kanban. Proficiency in automation tools and frameworks for continuous integration and delivery (CI/CD), and monitoring model performance in production environments.
- Cloud: Experience with cloud platforms (e.g. AWS, Azure, GCP) and containerization technologies like Docker and Kubernetes.
Experience:
- 3+ years of hands-on experience in designing and productionizing machine learning models and AI applications preferred.
- Bachelor’s degree or higher in a CS or quantitative discipline: Computer Science/ Math/Statistics/Engineering or equivalent experience.
- Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Demonstrated problem-solving and analytical thinking skills, with a focus on delivering practical and innovative solutions to answer business questions.
- Adaptability and willingness to embrace new technologies and challenges in a fast-paced and evolving environment.
