AI Automaion Expert / Data Science & AI ML Engineer

AI Automation Expert | Data Science, Machine Learning & AI-Powered Workflows Project Overview We are looking for a skilled **AI Automation Expert with strong experience in Data Science, Artificial Intelligence (AI), and Machine Learning (ML)** to design, develop, and implement intelligent automation solutions that streamline business operations, reduce manual work, and improve decision-making. The ideal candidate should be able to understand real-world business challenges and translate them into practical, scalable AI-powered solutions. You should have hands-on experience building automation workflows, integrating AI models and third-party APIs, processing and analyzing data, and deploying machine learning solutions that deliver measurable business value. Key Responsibilities **1. AI-Powered Workflow Automation** - Design and build intelligent workflows to automate repetitive, time-consuming business processes. - Connect different applications, databases, APIs, and business tools to create seamless automation pipelines. - Use AI to automate tasks such as document processing, data extraction, classification, summarization, report generation, and information handling. - Identify opportunities to replace manual processes with reliable, efficient automation systems. 2. AI Agents and Large Language Models (LLMs) - Develop AI agents and AI assistants that can understand requests, retrieve information, and perform specific tasks. - Integrate LLMs such as OpenAI GPT and other suitable AI models into business workflows. - Build retrieval-augmented generation (RAG) systems that allow AI applications to answer questions using company documents, databases, or internal knowledge bases. - Implement appropriate safeguards, validation, and error handling to improve the reliability of AI-generated outputs. **3. Data Science and Machine Learning** - Collect, clean, transform, and analyze structured and unstructured data. - Develop predictive models for forecasting, classification, customer behavior analysis, anomaly detection, and other business use cases. - Apply statistical analysis and machine learning techniques to identify patterns, trends, and actionable insights. - Evaluate model performance, improve accuracy where appropriate, and prepare models for practical deployment. **4. API Integration and System Development** - Integrate AI services, external APIs, databases, CRMs, and other business applications. - Build automation pipelines using tools such as n8n, Make, Zapier, or Python-based solutions, depending on project requirements. - Develop custom scripts and backend components where standard automation tools are insufficient. - Ensure workflows are maintainable, secure, scalable, and properly documented. **5. Testing, Optimization, and Deployment** - Test workflows and models against real-world scenarios. - Monitor performance, troubleshoot errors, and optimize execution speed and cost. - Implement logging, exception handling, and human approval steps where necessary. - Document the solution and provide guidance for ongoing maintenance and future improvements. ## Required Skills and Experience - Strong practical experience in AI automation and workflow development. - Solid knowledge of Data Science, Machine Learning, and statistical analysis. - Proficiency in Python and relevant libraries such as pandas, NumPy, scikit-learn, or similar tools. - Experience working with LLM APIs, prompt engineering, and AI application frameworks. - Experience integrating REST APIs, webhooks, databases, and third-party services. - Familiarity with automation platforms such as n8n, Make, or Zapier. - Understanding of data cleaning, model evaluation, testing, and deployment. - Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions. ## Nice to Have - Experience building AI agents, RAG pipelines, and document-processing systems. - Familiarity with vector databases and embedding models. - Experience with cloud platforms, Docker, and deploying AI applications. - Knowledge of business intelligence, forecasting, and predictive analytics. - Experience integrating AI solutions with CRM, ERP, marketing, sales, or customer-support systems. - Understanding of data privacy, security, and responsible AI practices. Expected Deliverables Depending on the project scope, deliverables may include: - A working AI automation workflow or AI-powered application. - Integrated APIs, AI models, and relevant business systems. - A predictive model or data analysis pipeline, where required. - Testing results and performance documentation. - Technical documentation, setup instructions, and handover support. How to Apply Please include the following in your proposal: 1. A brief overview of your experience with AI automation, Data Science, and Machine Learning. 2. Examples of similar projects you have completed, including your specific contribution and the results achieved. 3. The technologies and tools you would recommend for this type of work. 4. Your approach to understanding business requirements and developing a reliable solution. 5. Your availability, estimated timeline, and preferred pricing model. We value practical problem-solving, clear communication, and solutions that deliver measurable business outcomes. We are interested in building reliable AI systems that solve real problems—not just prototypes or demonstrations. Please share relevant portfolio projects or GitHub repositories where available.