About the roleAs a ML Engineer, you will be responsible for identifying patterns and generating insights from application and event data using supervised and unsupervised ML approaches.These insights will be critical to accelerating go-to-market strategies and operational performance in customer-centric organizations.You will play a key role in the development, training, and performance management of AI models, analyzing diverse datasets from sources such as application telemetry, CRM, support, accounting/billing, and web analytics.The position involves working closely with 1–5 customers as a highly trusted and billable AI/ML Engineer.Joining an early-stage AI startup, you will also contribute to the growth of delivery methodologies and AI/ML workbenches.ResponsibilitiesAggregate, analyze and generate supervised & unsupervised ML insights from large application telemetry data setsConsolidate and manage high-value datasets via REST APIs or Extract, Load, Transform (ELT) processes, etc into Datalakes such as Google BigQuery, Snowflake, DataBricks, AWS S3, etc.Build, train, test,



tune and deploy AI models at scale within a Customers' operating architecture in platforms such as Vertex AIEngage with other QuadSci deployed colleagues on the explanation of data insights, confirmation of design requirements, root cause analysis, etc.Work with Customers on AI feature roadmaps (incl. GenAI applications) for their models and ongoing performance management of deployed AI modelsCollaborate with QuadSci colleagues and / or Customer IT on integration and automation requirements reliant on AI/ML score code outputsQualificationsMust have a bachelor's degree in Computer Science, Data Science, Statistics, Mathematics or other related field3+ years of relevant experience in data science, consulting or product developmentExpertise in NumPy, Pandas, SciKitLearn, Keras, etc.Demonstrated success in the use of clustering, classification, regression, decision trees etc to deliver transformative insightsStrong experience in building, training, and tuning predictive machine learning, especially in the domains of next best offer or recommended action based on time-series type data setsExperience in Natural Language Processing (NLP) for sentiment analysis and behavioral modelingExtensive experience in SQL, Python, Pandas data transformation to form data tables and feature stores

📌 Data Scientist (México)
🏢 Talently
📍 México