Collaborated on multiple data science projects, focusing on machine learning, web scraping, and deployment using Flask applicationsPerformed data cleaning and preprocessing to handle missing values and outliersImplemented various machine learning algorithms including Logistic Regression, Support Vector Machine, and Random Forest etc.Conducted hyperparameter tuning and model evaluation using cross-validation techniques.Selected the best-performing model based on accuracy and other performance metrics.Developed a Flask application to provide an interactive web interface for usersIntegrated the machine learning model into the Flask app, ensuring seamless user experience.Analyse customer reviews to determine overall sentiment (positive, negative, neutral) using NLP and machine learningApplied NLP techniques such as tokenization, stop word removal, and stemming.Used TF-IDF Vectorizer to convert text data into numerical features for model training.

Gather relevant data sources including historical electricity prices, weather patterns, energy demand, market trends, and other relevant factors.Cleanse, preprocess, and normalize data to ensure consistency and accuracy for modeling purposes.Design and develop machine learning models and algorithms to predict electricity prices with high precision and reliability.Implement time-series forecasting techniques, regression models, and other advanced methodologies to analyze and interpret complex datasets.Explore and experiment with different modeling approaches, feature engineering techniques, and algorithms to enhance predictive performance.Conduct thorough evaluation and validation of developed models using appropriate metrics and methodologies.Perform back-testing and cross-validation to assess model robustness and generalization capabilities.Identify and address potential biases, limitations, and sources of error in the prediction process.

Gathered and extracted relevant data from various sources, ensuring accuracy and completeness.Processed and cleansed raw data to remove any anomalies or inaccuracies, preparing it for analysis.Utilized statistical tools and software to interpret data sets, identifying trends, patterns, and relationships.Summarized and visualized findings in clear and comprehensible reports or dashboards for higher-level analysts or stakeholders.

Developed data modeling guidelines and standardsMine and analyse large datasets, draw valid inferences, and present them successfullyMerged information with already-existing data sets while taking care to preserve historical records and datasetsResearched relevant key performance indicators for each problem statement and defined business requirements for data solutionsCreated data dashboards, graphs, and visualisations reports using Power BIPerformed thorough data validation, wrangling, and cleansing in Excel and/or SQL

Mine and analyse large datasets, draw valid inferences, and present them successfullyMerged information with already-existing data sets while taking care to preserve historical records and datasetsResearched relevant key performance indicators for each problem statement and defined business requirements for data solutionsCreated data dashboards, graphs, and visualisations reports using Power BIPerformed thorough data validation, wrangling, and cleansing in Excel and/or SQL

Managed projects from planning to execution, ensuring objectives were met within set timelinesEffectively communicated assessment findings to stakeholders and presented reports to groupsDesigned research studies, collected and analysed data, and developed predictive models.Proficient in Python, SQL, and machine learning frameworks for solving real-world problems.Analyse user support data to identify trends, patterns, and opportunities for improvement.Develop and maintain dashboards and reports to track key performance indicators (KPIs) and monitor IT support metrics.Utilize data visualization tools to communicate findings and insights to stakeholders in a clear and compelling manner.Collaborate with IT teams to identify root causes of support issues and develop proactive solutions to prevent recurrence.Conduct ad-hoc analyses to support business decisions and strategic initiatives.Assist in the design and implementation of IT support processes and workflows to improve efficiency and effectiveness.Research current and emerging trends and technologies in data analytics and IT support.

Handle first level support through answering incoming queries and help requests from end users, either via email or over the phone, using request fulfilment and incident management processes, in line with service desk defined SLA.Provide technical support, isolating, and resolving hardware and software problems involving applications, operating systems, communications infrastructure, and any other IT related challenges.Responsible for resetting user's passwords, provisioning, maintaining and removing security privileges for usersResponsible for accessing user's computer remotely to troubleshoot issues and make changes to their system settings where necessaryResponsible for documenting all calls, creating detailed notes of the user's problem and reviewing the user's level of satisfaction

Managed IT Infrastructure for day-to-day business operations and ensuring IT Operations ran smoothly 24x7Monitored the day-to-day functionality of end user’s computer health using SCCM server and deployed security patches periodically to boost performance and mitigate potential security loopholes.Supervised service improvement initiatives for disaster recovery, redundant IT architecture and inventory management. Frequently engaging with end-user to educate them on the need to be security conscious when performing their daily system operations