Cientista de Dados Sênior

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

As a Data Scientist with Advanced Analytics skills, you will leverage deep data and analytics expertise with strong business acumen to address business challenges. You will utilize data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes.

Your Primary Responsibilities Will Include

• Develop Predictive Models: Utilize mathematical optimization, discrete-event simulation, rules programming, and predictive analytics to forecast trends and suggest optimizations for improved business outcomes.
• Analyze Diverse Data Types: Effectively manage and analyze diverse data types and structures, ensuring data-driven decision-making and business optimization.
• Implement Data Visualization: Use data visualization tools like Matplotlib, Seaborn, and Plotly to communicate insights and recommendations to stakeholders.
• Apply Machine Learning Techniques: Apply machine learning, statistical modeling, and custom models to solve business problems in areas like supply chain management, pricing, risk assessment, and fraud detection.
• Optimize Business Outcomes: Use optimization tools like IBM CPLEX and Gurobi to identify opportunities for business improvement and implement solutions.
  
  

• Solid experience in Data Science and advanced data solutions within enterprise environments with strong proficiency in Python for analytics, data processing, and solution development;
• Hands-on experience with PySpark and Apache Spark;
• Advanced knowledge of the Hadoop ecosystem, including Hive;
• Experience with Apache Kafka and Event-Driven Architectures;
• Experience orchestrating data pipelines and workflows using Apache Airflow;
• Knowledge of Kubernetes and distributed computing environments;
• Experience designing and evolving enterprise Data Platforms;
• Strong understanding of Data Governance, data quality practices, and Metadata Management;
• Experience implementing data observability concepts and frameworks;
• Ability to provide technical leadership and support architectural decisions related to data ecosystems;
  
  

• Experience supporting clients within the Banking or Financial Services industry;
• Advanced SQL expertise;
• Experience with ETL and data integration frameworks;
• Background working with Data Warehouse solutions;
• Experience with IBM DataStage;
• Knowledge of Google BigQuery;
• Experience with DBT (Data Build Tool);
• Exposure to BI & Analytics initiatives;
• Experience with cloud-based data modernization and enterprise data transformation programs;