Data Analyst Machine Learning

Kareemuddin Mohammed Data Analyst

GA 470-***-**** ***************@*****.*** LinkedIn

SUMMARY:

Results-driven Data Analyst with 5+ years of experience leveraging Python, SQL, and advanced analytics to deliver actionable insights across networking, healthcare, e-commerce, and financial services industries. Proven expertise in designing real-time ETL pipelines using Kafka and Apache Spark, developing interactive dashboards with Power BI, Tableau, and Grafana, and implementing machine learning models that drive measurable business outcomes. Skilled in cloud platforms (AWS, Azure), database management (SQL Server, MySQL, MongoDB), and Cisco networking technologies including IOS XE telemetry and Catalyst Center integrations. Strong track record of collaborating with cross-functional teams to optimize data workflows, ensure regulatory compliance (HIPAA), and deliver insights that consistently improve operational efficiency by 20-50%. Combines technical proficiency in statistical analysis and data visualization with business acumen to translate complex data into strategic recommendations for C-level executives and stakeholders. EDUCATION:

Masters in Computer and Information Science Jan 2022 – Apr 2023 Jacksonville State University AL

Bachelor of Engineering in Computer Science and Engineering July 2017 – June 2021 Kakatiya Institute of Technology & Science India TECHNICAL SKILLS:

Languages: Python, R, SQL, Linux Bash, JavaScript, Scala Frameworks & Libraries:

Pandas, NumPy, Kafka, Airflow, SSIS, D3.js, Apache Spark, Hadoop, SciPy, Matplotlib, Seaborn, Scikit- learn, TensorFlow, Plotly, Streamlit

Database: Microsoft SQL Server, MySQL, PostgreSQL, MongoDB (NoSQL), Oracle, Redis, Snowflake, Visualization Tools:

Power BI, Tableau, Grafana, Excel (PivotTables, charts), Looker, QlikView, Interactive dashboard design, Google Data Studio, Jupyter Notebooks

Tools:

REST APIs, Excel Power Query, Git/GitHub, Jenkins, JIRA, Confluence, Postman, VS Code, PyCharm, Google Analytics, Firebase, SSRS, Cisco Catalyst Center, ThousandEyes Data Warehousing:

Data Lake design, AWS Redshift, AWS S3, AWS EMR, Azure Synapse, Azure Data Factory, Databricks, ETL/ELT processes, Data modeling, AWS Glue, Azure Blob Storage Project Management &

Collaboration:

Agile/Scrum methodology, Stakeholder collaboration, Cross-functional teamwork, Requirements gathering, Data governance, User Acceptance Testing (UAT), HIPAA compliance, SOX compliance EXPERIENCE:

Cisco – Data Analyst GA, USA June 2023 – Current

• Captured streaming telemetry from Cisco IOS XE/NX-OS devices via SNMP, NetFlow/IPFIX, and Syslog; integrated Catalyst Center and Secure Network Analytics exports into unified data lake, reducing data gaps by 30%.

• Interpreted networking protocols (BGP, OSPF, MPLS) and Cisco Stealthwatch schemas to validate telemetry integrity, ensuring accurate anomaly detection and compliance reporting for zero-trust architecture.

• Engineered real-time Python ETL pipelines (Kafka, Pandas) normalizing logs from Cisco Catalyst Center, Secure Network Analytics, and ThousandEyes, slashing manual data prep by 45%.

• Applied time-series analysis and clustering on Cisco IOS XE telemetry and NetFlow data to identify congestion patterns and Stealthwatch-flagged vulnerabilities, reducing incident rates by 20%.

• Conducted UAT with network architects and SOC analysts; refined Grafana dashboards integrating Catalyst Center APIs and ThousandEyes metrics, improving MTTD by 25%.

• Developed interactive Grafana panels displaying throughput trends and threat correlations from Cisco Secure Network Analytics and Cyber Vision, accelerating incident resolution by 50%.

• Collaborated with DevOps to benchmark ETL performance using DNA Center APIs and drafted AI-ready proposals, accelerating pipeline throughput by 35% for Cisco's AI infrastructure strategy.

• Generated compliance-ready reports integrating Cisco ISE policy data and Cyber Vision IT/OT profiling for audits and C-level reviews, delivering 100% accuracy within SLA deadlines. Adons Softech – Data Analyst India Apr 2019 – Dec 2021

• Designed automated ETL pipelines using Python (Pandas, NumPy) to extract client data from MySQL, SQL Server, and MongoDB databases for web/mobile applications, reducing data processing time by 40%.

• Analyzed user engagement metrics from Google Analytics, Firebase, and CRM systems for 50+ client projects across Healthcare, E- commerce, and Manufacturing sectors, improving user retention by 25%.

• Developed interactive Tableau dashboards tracking KPIs including user acquisition costs and conversion rates, increasing client satisfaction scores by 30% through data-driven insights.

• Performed statistical analysis and cohort analysis on e-commerce customer behavior using SQL and Python libraries (SciPy, Matplotlib), resulting in 20% improvement in conversion rates.

• Collaborated with development teams on API integrations and data collection strategies, establishing real-time reporting frameworks that improved project delivery efficiency by 35%.

• Created automated compliance reports for Healthcare and Financial Services clients using SSRS, ensuring HIPAA adherence and achieving 100% on-time delivery for regulatory submissions.

• Conducted A/B testing analysis on mobile app features using hypothesis testing and regression analysis, leading to UI/UX recommendations that increased user engagement by 45%.

• Built predictive models using machine learning algorithms (Random Forest, Logistic Regression) to forecast user churn and lifetime value, reducing churn rates by 15% across client portfolios.

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