Data Scientist
# Data Scientist **Infosys** · São Paulo, SP · `On-site` 🕒 **Статус:** *Опубликовано: вчера* · *Источник: Indeed* --- ### About the Role Infosys Brazil is looking for professionals with the profile of Data Scientist to join our team Main activities and responsibilities: - Shape the strategic direction and vision of Data Science across the organization by identifying transformative AI/ML opportunities and championing the team’s evolving role in a rapidly advancing GenAI landscape. - Lead the design and deployment of predictive and generative AI models that power personalization, pricing, search, and optimization in manufacturing domains. - Collaborate with product leaders to align ML initiatives with strategic business goals and drive product innovation through data-driven experimentation and modelling. - Architect scalable ML infrastructure and automated workflows using cloud-native tools (e.g., AWS, EC2, Kubernetes) to support efficient model training, deployment, and analytics across diverse datasets. - Ensure long-term performance and compliance of production AI models though robust governance and monitoring. - Provide technical leadership and mentorship to data scientists, shaping an innovative team culture and fostering high-performance and continuous learning. - Serve as a cross-functional technical leader, shaping company-wide technical initiatives beyond data science. Partner with engineering, product, and platform teams to influence architecture, innovation agendas, and technical standards across the organization. - Act as a senior technical advisor, leading resolution of complex modelling issues and acting as the escalation point for critical incidents. - Lead the exploration and strategic application of GenAI, identifying high-impact use cases and guiding their integration across products and platforms. Required Qualifications: Required: - Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics, or related discipline - 8+ years of experience in data science, machine learning, or applied AI, with a strong portfolio of high-impact projects in production - Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) - Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods - Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases - Strong hands-on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow) - Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning, and automated retraining - Hands of experience with design and analysis of A/B and multivariate experiments to measure the impact of product changes and business strategies with statistical rigor - Experience working with cloud environments like AWS and leveraging its offerings such as Lambda Bedrock, SageMaker, etc - Experience deploying and serving models through APIs (e.g., Flask, FastAPI) in both real-time and batch-processing environments - Excellent communication and stakeholder management skills, able to translate complex concepts into actionable insights for non-technical audiences - Demonstrated success mentoring teams, guiding technical strategy, and advocating for best practices in experimentation, reproducibility, and ethical AI - Experience working in agile product development environments (Scrum/Kanban); experience influencing product roadmaps is a strong plus Preferred: - Hands-on expertise in AI and LLM development with Finetuning expertise in a real-world business environment - Experience deploying AI models for real-time applications in manufacturing domain - Strong knowledge base of MLOps practices for efficient model deployment and scaling - Proven leadership and mentorship experience, with a passion for developing and inspiring high-performing teams - Contributions to open-source AI/ML projects, publications, or presentations at industry conferences - Design and manage reusable and consistent feature stores to improve model development efficiency. - Use DVC (Data Version Control) for experiment tracking and data lineage alongside Git. - Design and implement event-triggered systems (e.g., via AWS Lambda triggers) for ML operations. - Integrate ML models into serverless computing workflows for lightweight, on-demand inference. Additional information: Type of work : CLT, Flexible hours. Benefits package : Transport vouchers, meal vouchers, childcare assistance, life insurance, funeral assistance, medical and dental insurance. Career : Global work on national and international clients and/or projects, possibility of international career movement.
Наблюдалась 2026-10-15, впервые 2026-10-14, источник — Indeed.