Senior Data/Business Analyst with extensive experience as a technology-business professional who effectively translates operational needs into technical solutions. Equipped with analytics and reporting expertise to provide insights using data analysis. Versed in data mapping and user acceptance testing to solve complex problems in high-pressure environments. Strong analytical skills to investigate trends in large amounts of data and formulate conclusions based on findings. Excels at cultivating, managing, and leveraging client relationships to foster extended engagements and business opportunities.
I bring nine years of experience leading cross-functional data science and analytics teams. Proficient in cloud technologies such as AWS and GCP, I collaborate with data analysts, scientists, engineers, stakeholders, developers, and testers to implement innovative solutions. My expertise lies in leveraging data insights to drive revenue growth and uncover actionable trends for clients. With a strong focus on collaboration and client engagement, I oversee end-to-end project delivery while ensuring alignment with business objectives. My role involves strategic leadership, technical proficiency, and a commitment to delivering impactful data-driven solutions.
As a Senior Business Systems Analyst, I leverage expertise in business analysis methodologies to lead teams effectively. Utilizing project management tools like Asana, Jira, and Monday.com, I orchestrate tasks and ensure project alignment. Specializing in gathering requirements and acting as a liaison between stakeholders and technical teams, I foster clear communication and collaboration. Additionally, I implement KPIs and utilize CDM techniques to drive project success and facilitate data-driven decision-making processes. My role entails guiding teams in achieving project objectives while prioritizing efficiency and stakeholder satisfaction.
As a Lead Data Analyst, I utilize Python, SAS, and SQL for data analytics, integrating with big data technologies like Hadoop and Spark. Proficient in CRM (Salesforce) and ERP (SAP/Oracle) systems, I apply a range of machine learning algorithms and libraries such as Scikit-learn and TensorFlow for tasks including classification, linear regression, and NLP. Employing ML deployment tools like Airflow, MLflow, and Docker, I ensure a smooth transition of models to production. Additionally, I leverage AutoML solutions like SageMaker and Azure ML to streamline model development and deployment processes, driving actionable insights and optimizing business outcomes.
As a Data Management Analyst, I proficiently utilize tools spanning data management, visualization, mining, and data lake domains. I leverage Alteryx, MS Access, and RDBMS for efficient data handling and analysis. I create compelling visuals to convey insights by using visualization platforms such as Power BI, Tableau, and QlikView.With expertise in data mining tools like IBM SPSS or RapidMiner, I extract valuable patterns from complex datasets. Additionally, I design and maintain data lakes using technologies like Apache Hadoop or AWS S3, ensuring efficient and scalable data storage and retrieval while prioritizing data quality and integrity.
As a Data Consultant, I specialize in data manipulation, warehousing, governance, and VBA automation. Utilizing tools such as SQL, Python, and R, I adeptly manipulate and analyze data for insights. I design and maintain data warehouses using platforms like Snowflake or Amazon Redshift for scalable data storage and retrieval. Implementing data governance frameworks using tools like Collibra or Apache Atlas to ensure data integrity and compliance with regulations like GDPR and HIPAA. Additionally, I leverage VBA to automate tasks and enhance efficiency in data processing workflows.
As a data analyst with knowledge of ETL technologies and data stewardship, we use platforms such as Informatica, Talend, or SSIS to create and manage ETL processes. You ensure data quality by validating and cleansing it with tools like Trifacta or Dataiku, in addition to using SQL for querying and processing. Collaborating with teams and integrating several data sources using technologies such as SQL, Python, and Apache Spark. Make use of Excel for data analysis and reporting.
This project demonstrates how machine learning and NLP techniques can be applied to detect fake profiles on social media platforms, contributing to online security and trustworthiness. This code demonstrates the process of loading, preprocessing, and training models to detect fake social media profiles using both traditional machine learning (Random Forest) and deep learning (LSTM) techniques.
The project aims to predict housing prices using a basic linear regression model. Linear regression is a fundamental technique in machine learning used for predicting a target variable based on one or more predictor variables.
Professional Badminton Player
President - National Students' Union