Syed Ahsan Ali

• Designed and implemented scalable data pipelines for ingesting, processing, and storing massive datasets related to network performance analysis. Utilized tools like Apache Hadoop, Kafka, Apache Spark, and cloud storage solutions (e.g., AWS S3) to ensure efficient data.
• Developed and maintained data quality checks and data cleansing routines to ensure data integrity and accuracy for machine learning models. Leveraged tools like Apache Spark, SQL and Python libraries (Pandas, NumPy) to identify and rectify data inconsistencies, enabling reliable data-driven insights for Alpha AI's clients.
• Collaborated with data scientists and machine learning engineers to understand data requirements for various AI projects. Translated their needs into technical specifications and data pipeline designs, fostering seamless collaboration within Alpha AI's data science teams.
• Automated data analysis and reporting tasks using Python scripting and data visualization tools (e.g., Tableau, Power BI). Created interactive dashboards to effectively communicate key network performance metrics (KPIs) and customer insights to stakeholders at Alpha AI.
• Leveraged Snowflake and Databricks for advanced data processing and warehousing, implementing cloud-native solutions for telecom data management.

Designed and implemented scalable data pipelines for ingesting, processing, and storing massive datasets related to network performance analysis.
Utilized tools like Apache Hadoop, Kafka, Apache Spark, and cloud storage solutions such as AWS S3 to ensure efficient data processing.
Developed and maintained data quality checks and data cleansing routines to ensure data integrity and accuracy for machine learning models.
Leveraged Apache Spark, SQL, and Python libraries (Pandas, NumPy) to identify and rectify data inconsistencies, enabling reliable data-driven insights for Alpha AI's clients.
Collaborated with data scientists and machine learning engineers to understand data requirements for various AI projects.
Translated data requirements into technical specifications and data pipeline designs.
Automated data analysis and reporting tasks using Python scripting and data visualization tools such as Tableau and Power BI.
Created interactive dashboards to communicate key network performance metrics (KPIs) and customer insights to stakeholders at Alpha AI.
Leveraged Snowflake and Databricks for advanced data processing and warehousing.
Implemented cloud-native solutions for telecom data management.

Designed and implemented scalable data pipelines using Apache Spark and Hadoop to process large volumes of telecom network data.
Collaborated with cross-functional teams to develop data-driven solutions for network optimization, resulting in a 15% improvement in network performance.
Automated data validation and quality control processes to ensure data integrity and accuracy.
Conducted regular performance tuning and optimization of data processing workflows to improve efficiency and reduce latency.
Acted as a subject matter expert on data engineering best practices.
Provided training to team members on new tools and technologies.
Successfully employed cloud-based ETL/ELT tools including Apache Hadoop, Spark, and Kafka, and data modeling techniques.
Contributed to the creation of robust, real-time data solutions that facilitated data-driven insights for stakeholders.
Streamlined performance monitoring with automated reports for live network performance during special events like Super Bowl.

Developed predictive models to forecast network performance metrics and identify potential network outages using time series analysis and machine learning algorithms.
Applied advanced statistical techniques to analyze network KPIs and identify root causes of performance degradation, leading to a 20% reduction in network downtime.
Utilized SQL and Python to query and manipulate large datasets stored in AWS Redshift.
Maintained machine learning models for network traffic forecasting and anomaly detection using Python (NumPy, Pandas, Matplotlib, Scikit-learn).
Improved network resource allocation and ensured system stability.
Proficient in AWS cloud services including EC2 for scalable computing, EMR for big data analytics, and RDS for efficient database management.
Extensively utilized Redshift for high-performance data warehousing and AWS Glue for data integration.
Automated cell sites configuration data using Python by using different formulas to identify anomalies and configuration issues.
Fixed thousands of configuration issues which resulted in a 10% increase in network performance.
Effectively used Git/GitHub to manage collaborative projects, streamline workflows, and ensure code integrity and reliability.

Extracted data from different tools like ALPT, Sportfire, and LSM to perform data cleansing and preprocessing.
Used Python and SQL to transform data for statistical analysis.
Created dashboards and reports using Power BI and Tableau to visualize data and present findings to senior management.
Showed pre vs post KPI analysis after migration from Nokia to Samsung cell sites.
Collaborated with cross-functional teams to identify data needs and provide solutions.
Streamlined performance monitoring with automated reports.
Used Hadoop, Spark, and Kafka to manage, process, and derive insights from extensive data sets.

Identified, analyzed, and interpreted trends or patterns in complex data sets.
Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders.
Used statistical methods to analyze data and generate useful business reports.
Analyzed transactions to build logical business intelligence model for real-time reporting needs.
Analyzed data to identify root causes of problems and recommend corrective actions.