Role overview
- An advanced degree in a STEM-related field such as Mathematics, Statistics, Computer Science, Engineering, or a related field, or equivalent work experience.
- 5+ years of experience in Data Science or ML and AI with real-world data within a product development and/or research setting.
- Expertise in statistical analysis, ML modeling, experimentation, and optimization.
- Hands-on experience working with LLMs and AI agents, including fine-tuning, retrieval-augmented generation (RAG), and deploying models to enhance product features.
- A proactive mindset, a continual pursuit of new ideas and data sources, and the ability to systematically tackle ambiguous problems with a data-driven, hypothesis-based approach.
- Proficiency in Python and SQL, with experience using libraries such as Pandas, NumPy, Scikit-learn, and deep learning frameworks like TensorFlow or PyTorch.
- Experience working with Agent frameworks (e.g. google adk, LangChain) and AI agent evaluation
- Expert-level experience building and deploying data science products using cloud platforms (e.g., AWS, GCP) and MLOps tools.
- Strong project management experience and ability to work with a diverse, distributed, and talented group of people.
- Excellent written and verbal communication skills to explain technical concepts to non-technical stakeholders.
- Domain knowledge of large-scale, data-driven SaaS applications.
What you'll work on
- Identify opportunities to use advanced data science techniques leveraging a wide variety of MarTech data to solve problems and provide new insights to our customers.
- Develop and deploy AI/ML solutions, creating new products and value for our customers.
- Transform data science prototypes into scalable, production-ready, data-driven products in partnership with our infrastructure/engineering teams.
- Embed AI-powered features and automation tools in data science applications to improve velocity, product quality and customer experience as needed.
- Communicate the impact and outcomes of data science initiatives to stakeholders across the organization.
- Stay current with AI/ML advancements and continually seek for new ideas or paradigms that will add value to our customers.
Tags & focus areas
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