Data Science Engineering

SAI NAGA MANISH JUTURU

940-***-**** *********@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Data professional with over six years of experience spanning data science, data engineering, and analytics, delivering measurable impact in telecommunications, healthcare, and marketing domains. Skilled at transforming raw data into actionable insights, building scalable data pipelines, and applying AI/ML techniques to solve complex business problems. Proficient in Python, SQL, GCP, Snowflake, and big data tools, with a proven record of improving decision making, operational efficiency, and model performance in enterprise environments.

TECHNICAL SKILLS

Programming & Scripting: Python, SQL, R, Java, Bash, Scala, Shell Scripting

Data Engineering & ETL: Snowflake, BigQuery, Apache Airflow, Kafka, Spark, Hadoop, Dataproc, Dataflow, Informatica, HVR, Fivetran, Airbyte, Qlik, Apache NiFi

Databases: MySQL, PostgreSQL, Oracle, MongoDB, Cassandra, Redis

ML/AI & Analytics: TensorFlow, Scikit learn, PyTorch, Vertex AI, XGBoost, NLP, OpenCV, Keras, Pandas, NumPy, Statsmodels, Prophet

Visualization & BI Tools: Tableau, Power BI, Looker, Matplotlib, Seaborn, Plotly, D3.js, SSRS

Cloud Platforms: Google Cloud Platform (GCP), AWS (EC2, S3, RDS, Lambda), Azure (Data Factory, Synapse)

Big Data & Storage: Hive, HDFS, Parquet, Avro, Delta Lake

DevOps & CI/CD: Git, GitHub, GitLab CI/CD, Jenkins, Docker, Kubernetes, Terraform

Other Tools: Jupyter Notebook, VS Code, PyCharm, Postman, REST APIs, JSON, YAML

PROFESSIONAL EXPERIENCE

Data Scientist Comcast May 2023 – Present

Designed and maintained large scale data pipelines in Snowflake and GCP BigQuery to process and analyze subscriber behavior, network performance, and streaming content metrics for business insights.

Developed predictive analytics models to optimize content recommendations, improving viewer engagement by 18% and reducing churn rates in targeted customer segments.

Built interactive Tableau and Looker dashboards tracking network usage, service reliability, and customer satisfaction, enabling leadership to make data driven operational decisions.

Applied NLP techniques to analyze customer feedback from multiple channels, identifying key drivers of dissatisfaction and guiding service improvement initiatives.

Collaborated with engineering and product teams to deploy machine learning models into production using Vertex AI, ensuring scalability and reliability for millions of users.

Designed and deployed deep learning models to detect anomalies in network performance data, reducing outage detection time by 40%.

Fine tuned transformer based language models for automated classification and sentiment analysis of customer service transcripts, improving accuracy by 22% compared to baseline models.

Leveraged Apache NiFi and Airbyte for automated ingestion of real time network logs and customer interaction data into analytics pipelines, reducing manual integration time by 45%.

Data Engineer S&S Health Jul 2022 – May 2023

Designed and implemented robust ETL pipelines using Apache Airflow, Spark, Snowflake, and Apache NiFi to integrate healthcare claims, pharmacy, and patient data into a centralized repository.

Migrated on premises claims data warehouse to GCP using HVR and Fivetran for secure and high volume replication, reducing infrastructure costs by 25% and improving query performance by 40%.

Created optimized SQL schemas to handle high volume structured and semi structured medical data, ensuring faster data retrieval and scalability for analytics workloads.

Developed automated data validation and anomaly detection scripts to identify potential billing errors and fraudulent claims, reducing manual review time by 30%.

Partnered with data science teams to build predictive models for patient risk scoring, achieving an 87% accuracy rate in identifying high risk cases.

Data Engineer Dentsu May 2019 – Dec 2021

Engineered and maintained real time streaming and batch data pipelines using Apache Airflow, Kafka, Spark, and Fivetran, processing 5TB+ of marketing data daily for analytics and campaign optimization.

Integrated diverse marketing and CRM datasets into Snowflake and GCP BigQuery, creating a centralized, analytics ready repository that provided a unified customer view for stakeholders.

Optimized SQL queries, indexing, and partitioning strategies, reducing query execution times by over 60% and delivering an annual compute cost saving of $80K.

Automated ETL workflows through Airflow DAGs, Apache NiFi, and HVR, reducing manual intervention by 95%, minimizing operational bottlenecks, and increasing delivery speed for analytics teams.

Collaborated with data science teams to generate feature rich datasets for advanced predictive modeling, improving ad targeting accuracy by 18% and campaign ROI.

Data Analyst Deloitte Apr 2018 – Apr 2019

Performed comprehensive financial data analysis for compliance and regulatory projects, increasing audit accuracy by 12% and improving the efficiency of risk detection.

Developed SQL based data marts to consolidate and streamline compliance data, reducing reporting turnaround from three days to four hours and increasing audit readiness.

Designed and automated interactive Power BI dashboards that allowed senior auditors to track compliance metrics in real time, eliminating the need for manual reporting cycles.

Partnered with cross functional teams to define key performance indicators (KPIs) and establish standardized reporting frameworks, ensuring consistent monitoring across all compliance projects.

Built data validation and anomaly detection scripts to identify inconsistencies in transactional data, improving accuracy by 15% and reducing manual data cleaning efforts.

EDUCATION

Master of Science in Information Systems and Technologies – University of North Texas

Bachelor of Computer Science and Engineering – GITAM University

CERTIFICATIONS

Google Cloud Certified – Associate Cloud Engineer

Snowflake SnowPro Core Certification

Google Cloud Professional Data Engineer Certification

PROJECTS

Fraud Detection with Vertex AI – Built and deployed a machine learning pipeline on GCP to detect fraudulent credit card transactions in real time with 92% precision.

Healthcare Data Warehouse Migration – Led the migration of claims data from on premise SQL Server to Snowflake on GCP, reducing query time by 45%.

Customer Churn Prediction – Created a churn prediction model using Python and XGBoost for a telecom client, increasing campaign ROI by 20%.

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