Senior AI/ML Engineer & Data Scientist

Danish Sharma

*********@*****.*** +1-469-***-****

**** ******** ** **********, ** 78628

Professional Summary

Senior Data Scientist with 10+ years of experience in machine learning, statistical modeling, and big data analytics, dedicated to transforming complex data into actionable insights. Expertise in Python, R, SQL, and visualization tools like Tableau and Power BI, with a strong record of developing predictive models that drive business growth. Skilled in collaborating with stakeholders to identify data-driven opportunities and delivering high-impact solutions in dynamic environments.

Experience

Senior AI/ML Engineer / Sabre Corporation Apr 2022 - Jun 2026 Southlake, TX / Full-time

• Architected and deployed end-to-end machine learning pipelines that process over 50 million records daily, reducing model training time by 40% and enabling real-time decision-making for travel and hospitality clients.

• Developed predictive models using gradient boosting and deep learning to forecast demand and optimize pricing, resulting in a 15% increase in revenue across key product lines.

• Led a team of 5 data scientists in designing and implementing a customer churn prediction system, achieving a 25% improvement in retention rates through targeted interventions.

• Collaborated with business stakeholders to translate complex business requirements into data science projects, delivering actionable insights that informed strategic planning and operational improvements.

• Implemented automated data validation and testing frameworks to ensure data quality and integrity, reducing data errors by 30% and increasing trust in analytics outputs.

• Built interactive Tableau dashboards and Power BI reports to visualize key performance indicators, enabling executives to monitor business health and identify trends in real-time.

• Optimized big data processing using Apache Spark and Hadoop, cutting data processing time by 50% and enabling analysis of terabyte-scale datasets.

• Mentored junior data scientists and engineers, fostering a culture of continuous learning and improving overall team productivity by 20%.

• Stayed current with emerging technologies and industry trends, introducing new machine learning frameworks and tools that enhanced model accuracy and scalability. Senior AI/ML Engineer / BMC Software Jun 2020 - Mar 2022 Houston, TX / Full-time

• Designed and implemented machine learning models to detect anomalies in IT infrastructure monitoring data, reducing false positives by 35% and improving incident response times.

• Performed exploratory data analysis on large datasets using Python and R, uncovering patterns and insights that guided product development and customer success initiatives.

• Developed a recommendation engine for software asset management, increasing upsell opportunities by 18% through personalized product suggestions.

• Collaborated with cross-functional teams to define data requirements and build scalable data pipelines in Spark, ensuring timely and accurate data availability for analytics.

• Created interactive Power BI dashboards to track product usage and customer satisfaction, enabling data-driven decisions that improved user engagement by 12%.

• Conducted A/B testing and statistical analysis to evaluate the impact of new features, providing evidence-based recommendations to product managers.

• Automated data quality checks and implemented monitoring systems, reducing data inconsistencies by 25% and ensuring high data integrity.

Machine Learning Engineer / Salesforce Jun 2019 - Apr 2020 San Francisco, CA / Full-time

• Developed and deployed machine learning models for lead scoring and opportunity forecasting, improving sales conversion rates by 20%.

• Engineered features from customer interaction data using SQL and Python, enhancing model predictive power and business relevance.

• Built real-time data pipelines using Kafka and Spark Streaming to feed models with up-to-date information, enabling dynamic decision-making.

• Designed intuitive Tableau dashboards to visualize model performance and business metrics, facilitating transparency and stakeholder alignment.

• Collaborated with data engineers to optimize data storage and retrieval processes, reducing query latency by 30%.

• Participated in code reviews and contributed to the development of best practices for model deployment and monitoring.

Data Scientist / EverString Aug 2015 - May 2019

San Mateo, CA / Contract

• Analyzed complex firmographic and behavioral data to build predictive models for B2B lead generation, increasing lead qualification accuracy by 25%.

• Utilized data mining techniques to extract actionable insights from unstructured data sources, supporting the development of new product features.

• Developed and maintained ETL processes in Python and SQL to ensure data accuracy and availability for analytics and modeling.

• Created data visualizations and reports using Tableau and matplotlib, clearly communicating findings to non-technical stakeholders.

• Performed statistical analysis and hypothesis testing to validate model assumptions and ensure robust performance.

• Collaborated with engineering teams to integrate machine learning models into production systems, ensuring seamless deployment and scalability.

• Championed data quality initiatives, implementing validation checks that reduced data anomalies by 20%. Technical Skills

Machine Learning & Statistics: Supervised Learning, Unsupervised Learning, Regression Analysis, Classification, Clustering, Time Series Forecasting, Ensemble Methods, Feature Engineering, Model Evaluation, Statistical Testing Programming Languages: Python, R, SQL, PySpark, Scala, Java, Bash Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, ggplot2, Plotly, D3.js Big Data Technologies: Hadoop, Spark, Hive, Pig, Kafka, Flume, HBase, Cassandra, Snowflake, AWS EMR Data Mining & Modeling: Data Wrangling, ETL Pipelines, Data Cleaning, Dimensional Modeling, Data Warehousing, Data Validation, Data Quality, Data Integration, NoSQL Databases, Relational Databases Cloud & DevOps: AWS, Azure, GCP, Docker, Kubernetes, Jenkins, Git, Airflow, Terraform Business Intelligence: Dashboard Design, KPI Tracking, Data Storytelling, Root Cause Analysis, A/B Testing, Data-Driven Decision Making, Stakeholder Management, Requirement Gathering Education

Master of Science in Computer Science and Engineering / Santa Clara University Aug 2016 - May 2018 Bachelor's Degree in Computer Science / San José State University Sep 2011 - Jun 2015 Certifications

• Certified Data Scientist, Data Science Council of America (DASCA) Jan 2022 - Jan 2025

• AWS Certified Machine Learning – Specialty, Amazon Web Services Jun 2020 - Jun 2023

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