Job Summary: We are looking for an AI Integration/BI Developer to bridge AI capabilities with business intelligence, driving insights and enhancing data-driven decision-making across the organization. This role involves designing, developing, and integrating AI and BI solutions, building data pipelines, and creating visualizations that turn complex datasets into actionable insights. The ideal candidate has a strong background in data engineering, AI/ML integration, and BI development, with a focus on ensuring seamless data flows and effective model deployment. Key Responsibilities: Data Integration and ETL: Design and implement ETL pipelines to integrate data from various sources, ensuring it is prepared for AI and BI applications. AI Model Integration: Collaborate with data scientists to integrate machine learning models into business workflows and BI tools (e.g., Tableau, Power BI). Business Intelligence Development: Develop dashboards, reports, and visualizations that provide actionable insights, using BI tools to translate AI-driven data into meaningful formats. Data Pipeline Automation: Automate data processing workflows to support continuous integration and delivery of AI models, ensuring real-time data availability. Collaboration: Work closely with data science, analytics, and IT teams to understand business needs, provide solutions, and optimize data architecture. Performance Monitoring: Monitor the performance and accuracy of AI models in production, providing support for model retraining and updates as needed. Documentation and Compliance: Maintain documentation for data integration processes, model integration workflows, and BI reporting standards. Qualifications: Education: Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field. Advanced degree or certifications in AI, BI, or data engineering are a plus. Experience: 3 years in BI development, data integration, or data engineering, with experience in AI/ML model integration. Technical Skills: ETL Tools: Proficiency in ETL tools (e.g., Talend, Informatica, Apache NiFi) and data integration frameworks. Programming Languages: Strong skills in SQL, Python, and experience with ML libraries (e.g., scikit-learn, TensorFlow). BI Tools: Proficiency in BI and visualization tools such as Power BI, Tableau, or Looker. Cloud & Big Data: Experience with cloud platforms (AWS, Azure, GCP) and big data tools (Spark, Hadoop). APIs and Integration: Familiarity with RESTful APIs and other integration methods for embedding AI models into applications and BI tools. Soft Skills: Strong analytical skills, problem-solving abilities, and effective communication. Nice-to-Have: Experience with MLops and data versioning tools (MLflow, DVC). Familiarity with natural language processing (NLP) or computer vision. Understanding of data governance and compliance standards (GDPR, HIPAA). Experience in deploying AI models in real-time or streaming environments.