Senior Data Scientist

hace 3 semanas

Mexico City finvero A tiempo completo

Senior Data Scientist - Risk We are looking for a Data & AI Engineer to design, build, and scale advanced data pipelines and AI-driven systems. This role sits at the intersection of data engineering, machine learning, and production AI, enabling real-time analytics, predictive models, and intelligent automation across the organization. About the Role You will work closely with product, engineering, and business teams to transform raw data into high-impact AI solutions. Key Responsibilities Design, build, and maintain scalable data pipelines (ETL/ELT) for structured and unstructured data. Develop, deploy, and monitor machine learning and AI models in production. Implement real-time and batch data processing architectures. Optimize data storage solutions (Data Lakes, Warehouses, Feature Stores). Ensure high data quality, reliability, governance, and security standards. Build end-to-end MLOps pipelines: training, versioning, deployment, monitoring, and retraining. Collaborate with Data Scientists, Product Managers, and Software Engineers. Optimize model performance, cost efficiency, and system scalability. Document architectures, workflows, and best practices. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI, or related field. 3+ years of experience in Data Engineering, Machine Learning Engineering, or AI Systems. Strong programming skills in Python and SQL. Hands‑on experience with ML frameworks (TensorFlow, PyTorch, Scikit‑learn). Experience with cloud platforms (AWS, GCP, or Azure). Knowledge of data pipelines & orchestration tools (Airflow, Dagster, Prefect). Experience with containerization and deployment (Docker, Kubernetes). Solid understanding of APIs, microservices, and distributed systems. Nice to Have Experience with LLMs, Generative AI, and vector databases (OpenAI, LangChain, Pinecone, Weaviate). Knowledge of streaming systems (Kafka, Spark Streaming). Financial, fintech, e‑commerce, or risk modeling domain experience. Experience with feature engineering platforms and real‑time inference. Key Skills Data Architecture Machine Learning Engineering MLOps Cloud Infrastructure Big Data Processing Generative AI Automation & Scalability What We Offer Competitive salary + performance bonuses Stock options / ESOP (if applicable) Flexible working model High‑impact projects with real‑world AI deployment Continuous learning budget Success Metrics (First 6–12 Months) Production‑grade AI pipelines deployed Reduced model deployment time Improved data reliability and model performance Scalable AI infrastructure operational #J-18808-Ljbffr

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