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Senior Machine Learning Engineer | Data Scientist
Phone: PHONE NUMBER AVAILABLE
Email: EMAIL AVAILABLE
Address: Rochester New York, United States, Street Address
Professional Summary:
Results-oriented Senior Machine Learning Engineer and Data Scientist with 8 years
of experience in developing and deploying cutting-edge machine learning models
and AI-driven solutions. Adept at applying advanced methodologies to solve complex
business challenges, driving impactful outcomes across diverse industries such as
finance, travel, e-commerce, and industrial operations. Proven expertise in utilizing
data-driven strategies to optimize processes, enhance operational efficiency, and
support decision-making. Demonstrated success in leading high-impact projects
from conception to deployment, collaborating with cross-functional teams, and
leveraging innovative techniques to deliver scalable, production-ready solutions.
Recognized for a strong ability to adapt in fast-paced environments and deliver
measurable improvements in business performance.
Technical Skills:
Programming: Proficient in Python, R, SQL, Java, Scala, MATLAB; expertise in
machine learning frameworks like TensorFlow, Keras, PyTorch, and libraries such as
Scikit-learn, XGBoost, LightGBM, and CatBoost.
Machine Learning: Hands-on experience with Supervised, Unsupervised, and
Reinforcement Learning; skilled in Deep Learning (CNN, RNN, LSTM), Gradient
Boosting, Decision Trees, Random Forest, SVM, KNN, and K-Means algorithms.
NLP: Expertise in Natural Language Processing with NLTK, SpaCy, Gensim, and
Huggingface Transformers for text classification, sentiment analysis, and entity
recognition.
Cloud Platforms: Extensive experience in cloud-based solutions using AWS
(SageMaker, EC2, Lambda) and Microsoft Azure for scalable AI/ML deployments.
Data Science Tools: Advanced skills in data manipulation, visualization, and
analytics with Pandas, NumPy, Dask, Matplotlib, Seaborn, Plotly, and Tableau for
real-time insights and decision-making.
Work Experience:
Senior Machine Learning Engineer / Data Scientist
Tech Company | 02-2021 - Present
Engineered and deployed AI-driven recommendation systems using TensorFlow
and PyTorch, significantly boosting user engagement and personalization
through advanced algorithms and model optimization.
Developed and optimized demand forecasting models with Random Forest and
Gradient Boosting, enhancing inventory management efficiency by 20% and
streamlining supply chain operations.
Designed and implemented sophisticated deep learning architectures, including
CNNs and LSTMs, for high-accuracy text and image classification, increasing
predictive performance and data insights.
Applied cutting-edge NLP techniques for sentiment analysis and customer
segmentation using SpaCy and NLTK, driving actionable insights and informing
strategic decision-making.
Led cross-functional teams in integrating machine learning solutions into
production environments, ensuring scalability and aligning with business
objectives for enhanced operational outcomes.
Machine Learning Engineer
AI Startup | 12-2018 - 02-2021
Developed and optimized dynamic pricing models using SVM and K-Means
clustering, resulting in a 25% increase in revenue and enhanced pricing strategies.
Engineered predictive maintenance solutions with Random Forest, reducing
equipment downtime by 15% through advanced anomaly detection.
Implemented time series forecasting models (ARIMA, LSTM) for demand
prediction, achieving an 18% improvement in forecasting accuracy and
streamlined inventory management.
Designed and deployed computer vision models using CNN for product
categorization, improving catalog efficiency and enhancing product discovery.
Data Scientist
Data Solutions Company | 05-2016 - 11-2018
Developed advanced fraud detection models using K-Means clustering and
ensemble techniques, boosting detection accuracy by 30% and enhancing security
measures.
Designed and implemented recommendation systems with collaborative filtering,
significantly improving user engagement and retention rates.
Automated data preprocessing and feature engineering workflows utilizing
Python and SQL, leading to a 40% reduction in manual data handling and
increased efficiency.
Conducted comprehensive A/B testing and statistical analysis to rigorously
validate model performance and drive data-driven decision-making.
Leveraged machine learning algorithms to uncover actionable insights from large
datasets, contributing to strategic business improvements.
Enhanced model performance through iterative optimization and validation,
ensuring robust and reliable data solutions.
Education:
Bachelor of Science in Computer Science
University of Houston Texas
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