• Designing and developing machine learning systems and algorithms: This involves choosing the right algorithms, frameworks, and tools for the specific problem at hand.• Data wrangling and preparation: Cleaning, transforming, and structuring data to feed into the models effectively.• Training and evaluation: Setting up the training process, monitoring performance, and fine-tuning models for optimal accuracy andgeneralizability.• Experimentation and iteration: Running tests, analyzing results, and continuously improving the models.• Building and deploying ML pipelines: Creating the infrastructure to move data through the various stages of the ML process.• Monitoring and maintenance: Tracking model performance in production, identifying issues, and making necessary adjustments.• Working with data scientists and other stakeholders: Understanding business needs, translating them into technical requirements, and communicating progress effectively.• Automating ML processes: Building systems to streamline the ML lifecycle.

• Designing and Implementing AI Models and Algorithms:- You are responsible for developing novel AI models and algorithms. This involves designing and implementing machine learning models that can process data and make predictions or classifications.• Analyzing Large Datasets:- AI Developers work with large datasets to identify patterns, trends, and insights. Analyzing data is essential for training and improving existing AI systems.• Creating and Maintaining Databases for AI-Powered Systems:- You'll design and manage databases that store data used by AI applications. These databases are critical for efficient data retrieval and model training.• Collaborating with Software Developers:- AI models need to be integrated into broader software systems. You'll work closely with software developers to ensure seamless integration and functionality.• Cross-Functional Collaboration:- AI Developers often collaborate with data scientists, data engineers, and other tech teams. Understanding project requirements and creating viable solutions require cross-functional teamwork.• Alignment with Business Strategy:- Working with data scientists, you'll ensure that AI systems align with broader business goals and strategy. This involves understanding the business context and tailoring AI solutions accordingly.• Advising on Legal and Ethical Considerations.

• Conducted data analysis to inform business decisions, leading to a 15% increase in operational efficiency.• Developed and maintained dashboards and reports using SQL and Tableau to visualize key performance indicators.• Collaborated with cross-functional teams to improve data quality, resulting in a 10% reduction in data discrepancies.• Led a customer data analysis project to assess satisfaction with services, providing actionable insights that increased customer satisfaction by 20%.

• Technical Support: Troubleshoot internet connectivity issues, slow speeds, and other technical problems customers may face with their ADSL connection.• Installation Assistance: Help customers with setting up their ADSL modem/router, providing guidance on installation, and configuration of the connection.• Service Monitoring and Outage Management: Keep track of the service quality, identify outages, and inform customers of ongoing maintenance or issues affecting their internet service.• Billing and Account Management: Handle customer queries related to bills, payments, service plans, and other account-related issues.• Service Upgrades and Downgrades: Assist customers in upgrading or downgrading their internet plans, and provide information on new offers or packages.• Customer Education: Guide customers on optimizing their internet usage, securing their connection, and avoiding unnecessary data usage.• Escalation of Complex Issues: For complex problems that cannot be resolved at the customer service level, escalate the issue to specialized technical teams.• Follow-up: After resolving issues, follow up with customers to ensure satisfaction and provide additional support if needed.

• Keyword research: Identifying relevant keywords with high search volume and low competition to target.• Title tag and meta description optimization: Creating compelling and informative snippets that accurately reflect the page content and attract search engine clicks.• Internal linking: Strategically linking between relevant pages on the website to improve website structure and user navigation.• Image optimization: Using alt tags and descriptive filenames to improve image search visibility.• Technical SEO audits: Identifying and fixing technical issues that may hinder search engine visibility, such as broken links, slow loading times, or crawl errors.