to the continuous improvement of development processes, including CI/CD and automated deployment pipelines. Required Skills & Experience Strong proficiency in Python, with experience in libraries such as Pandas, NumPy, and application frameworks (e.g., Flask, FastAPI, or similar). Solid understanding of software engineering principles, including object-oriented design and modular architecture. Experience building applications for front office environments within More ❯
building, deploying and maintaining NLP/Deep Learning Systems. * Extensive experience in at least one Deep Learning framework (PyTorch, TensorFlow, JAX). * Well versed in the scientific Python ecosystem (NumPy, Scikit-Learn, Pandas etc.). * Strong Data Engineering underpinnings and an ability to work with big data (Tbs). * Strong leadership skills, using empathy, clarity and challenge to support your More ❯
reusable analytical datasets. Modern BI: hands-on experience with a modern BI platform with integrated semantic layer (e.g Omni, Looker, Thoughtspot) Python for analysis: practical experience with pandas/numpy and notebook-based workflows for LTV, attribution, simulations and experimentation analysis. Domain expertise: deep, practical knowledge in one or more of the following functions & platforms: CRM (e.g. SalesForce), marketing (e.g. More ❯
dashboards and visualizations for business teams Communicate findings to non-technical stakeholders What You Bring 5+ years in applied data science or analytics Strong Python or R skills (pandas, NumPy, Jupyter) and solid SQL experience Familiarity with BI tools like Tableau or Power BI Strong foundation in statistics, experimentation, and A/B testing Excellent communication and storytelling abilities Role More ❯
