Siddharth Srinivasan work email
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Experienced Analytics Engineer with over 7 years of hands-on experience specializing in the full spectrum of data management and analytics processes. My expertise spans across key areas including data extraction, requirement gathering, data modeling, statistical modeling, data mining, and data visualization. I have successfully applied these skills in various methodologies such as SDLC, Agile, and Waterfall, consistently delivering robust solutions tailored to meet organizational needs.My technical proficiency includes advanced knowledge of Spark for large-scale data processing, coupled with extensive experience in designing and optimizing data warehousing solutions. I am proficient in programming languages including Python, R, and SQL, using them to develop sophisticated analytics pipelines and implement complex data transformations.I am well-versed in utilizing a wide array of data science libraries such as NumPy, Pandas, Matplotlib, SciPy, and ggplot2, enabling me to conduct in-depth analysis and visualization of data insights. Moreover, my experience with cloud platforms such as AWS, Azure, and GCP has allowed me to deploy scalable and efficient data solutions, contributing to significant improvements in data processing efficiency and query response times.In addition to technical skills, I have a strong foundation in product management, SLA planning, and mentoring junior team members. I excel in fostering collaboration across cross-functional teams and stakeholders, ensuring alignment with business objectives and delivering high-quality analytics solutions on time and within budget.My commitment to excellence extends to continuous learning and professional development, evidenced by my educational background in Computer Information Systems and certifications in cloud technologies and data analytics.I am passionate about leveraging data-driven insights to drive business growth and innovation. I am eager to bring my expertise and enthusiasm to a dynamic team, where I can contribute to solving complex challenges and driving strategic decision-making through advanced analytics and engineering solutions.
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Data EngineerHollywood FeedAustin, Tx, Us
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Bi Analytics EngineerAnt Savings Corp Dec 2023 - Present Architected data infrastructure using Azure Data Factory and Snowflake, integrating diverse real estate data sources. Improved data accessibility by 35%, enabling advanced predictive analytics for property valuation and risk assessment. Developed ETL processes using SSIS and Python, implementing custom data cleansing algorithms. Reduced data processing time by 40% and ensured 99.9% data integrity for real estate analytics. Designed Power BI dashboards visualizing key real estate metrics, leading to a 25% increase in data-driven decision-making for property acquisition and pricing strategies. Implemented data quality checks using Azure Data Quality Services, adhering to GDPR and CCPA. Reduced data discrepancies by 30%, enhancing customer trust and regulatory compliance. Utilized Git and Azure DevOps for CI/CD, implementing automated testing and blue-green deployment. Reduced BI solution deployment time by 50% while minimizing service disruptions. -
Bi Analytics EngineerInfostretch Aug 2021 - Sep 2023Santa Clara, California, Us Engineered data pipelines using Azure Data Factory for hourly ingestion of customer data. Implemented delta load strategies, improving data freshness for multiple e-commerce companies. Optimized PySpark scripts in Databricks, processing terabytes of shipping data daily. Reduced data processing time and enabling real-time analytics for shipment tracking and delivery estimation. Implemented K-means clustering in Snowflake SQL to group shipping patterns. Reduced bulk mail shipping costs by 20% and optimized last-mile delivery routes across client companies. Created automated PowerBI reports with row-level security, deployed via Azure App Service. Ensured secure, daily distribution of customer-specific analytics while maintaining data privacy. Utilized dbt for data transformation and documentation, improving lineage tracking. Reduced time spent on data governance, enhancing ability to trace data origins and resolve discrepancies. -
Sr. Ml Data Analyst / Team LeadAmazon Jun 2018 - Aug 2019Seattle, Wa, Us Led a team of 8 analysts on an Alexa Analytics project, implementing Agile methodologies with bi-weekly sprints and daily stand-ups. Implement JIRA for project management and story point estimation, resulting in a 25% increase in team productivity and consistent on-time project delivery. Developed ensemble machine learning models using AWS SageMaker and scikit-learn to improve Alexa's natural language processing capabilities. Implemented a novel approach combining BERT for intent classification and LSTM for entity recognition, contributing to increase in successful user interactions, particularly for complex, multi-turn dialogues. Created Tableau dashboards to visualize Alexa performance metrics and user interaction patterns. Implemented funnel analysis to identify drop-off points in user interactions, providing actionable insights that led to a 15% improvement in user satisfaction scores and a 10% increase in daily active users. Executed data quality monitoring using AWS Glue DataBrew, creating custom validation rules based on domain expertise. This reduced data anomalies by 40%, ensuring high-quality inputs for Alexa's machine learning models and improving the accuracy of voice recognition in noisy environments. Utilized AWS QuickSight to develop real-time analytics dashboards for stakeholders, focusing on key performance indicators such as intent recognition accuracy and user engagement metrics. This enabled data-driven decision-making in feature prioritization, contributing to a 6% enhancement in Alexa's overall goal success rate and a 12% increase in user retention. -
Data AnalystAmazon Nov 2016 - Jun 2018Seattle, Wa, Us Leveraged AWS Glue, Redshift, and S3 to transform unstructured and semi-structured data for Alexa development. Implemented custom ETL jobs to handle various audio file formats and transcription outputs, improving data processing efficiency and enabling more accurate analysis of user speech patterns. Developed ETL workflows using AWS Step Functions and Lambda, creating a serverless architecture for data preparation processes. Implemented error handling and retry mechanisms, reducing manual intervention by 50% and ensuring 24/7 data availability for downstream analytics. Utilized Python and pandas for data cleaning and preprocessing, implementing statistical analysis techniques such as outlier detection using Interquartile Range (IQR) and Z-score methods. This resulted in a 25% improvement in model training data accuracy, particularly for rare intents and edge cases. Created complex SQL queries in Amazon Redshift for data transformation and analysis, optimizing for star schema design. Implemented materialized views for frequently accessed data, contributing to an increase in Alexa's accuracy from 86% to 93% for multi-lingual queries. Implemented version control for analytics scripts using Git and AWS CodeCommit, establishing a branching strategy aligned with feature development. This improved collaboration among data scientists and reduced code conflicts, accelerating the deployment of new Alexa skills
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Data AnalystDell Technologies Sep 2015 - Nov 2016Round Rock, Texas, Us Designed and implemented ETL pipelines using AWS Glue and SSIS, integrating data from diverse sources including CRM systems, ERP databases, and flat files into Amazon Redshift. Overcame challenges in data type mismatches and inconsistent naming conventions, resulting in a 40% improvement in data accessibility for analytics teams. Developed predictive models using TensorFlow and scikit-learn for product demand forecasting, deployed on AWS SageMaker. Implemented a novel approach combining time series analysis (ARIMA) with machine learning (Random Forests), leading to a 20% increase in forecast accuracy and optimizing inventory management across multiple product lines. Created interactive Tableau and Power BI dashboards, visualizing key business metrics such as sales pipeline, customer churn risk, and product performance. Implemented drill-down capabilities and cross-filtering, enabling real-time monitoring of KPIs and resulting in a 30% reduction in time-to-insight for decision-makers in sales and marketing departments. Implemented automated reporting solutions using SSRS and Python scripts on AWS Lambda, creating a scalable system that adapts to varying data volumes. Integrated email notifications for report completion and error alerts, reducing manual report generation effort and ensuring timely delivery of insights to stakeholders across different time zones. Optimized Redshift query performance through careful schema design and query tuning, implementing distribution keys based on join patterns and sort keys for frequently filtered columns. Utilized the EXPLAIN command to identify bottlenecks, achieving a reduction in average query execution time and improving overall system responsiveness for concurrent users.
Siddharth Srinivasan Skills
Siddharth Srinivasan Education Details
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Colorado State UniversityComputer Information Systems -
Anna University ChennaiComputer Science
Frequently Asked Questions about Siddharth Srinivasan
What company does Siddharth Srinivasan work for?
Siddharth Srinivasan works for Hollywood Feed
What is Siddharth Srinivasan's role at the current company?
Siddharth Srinivasan's current role is Data Engineer.
What is Siddharth Srinivasan's email address?
Siddharth Srinivasan's email address is si****@****ail.com
What schools did Siddharth Srinivasan attend?
Siddharth Srinivasan attended Colorado State University, Anna University Chennai.
What are some of Siddharth Srinivasan's interests?
Siddharth Srinivasan has interest in Environment, Photographytraveladventure Sports, Photography, Science And Technology, Photography Travel Adventure Sports, Animal Welfare, Travel, Adventure Sports.
What skills is Siddharth Srinivasan known for?
Siddharth Srinivasan has skills like Social Media, Social Media Marketing, Market Planning, Market Analysis, Microsoft Office, Digital Marketing, Statistics, Marketing Strategy, Forecasting, Adobe Creative Suite, Marketing Communications, Qualitative Research.
Who are Siddharth Srinivasan's colleagues?
Siddharth Srinivasan's colleagues are Reggie Pederson, Kurt Bruggeman, Madelyn Brashear, Allyson Meehan, Jeremy Jackson, Kenneth Wyman, Kathy Killy.
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