About me

machine learning engineer

Rodrigo Gonzalez is a seasoned Data Scientist and Machine Learning Engineer with a rich history of leveraging data-driven solutions to drive business improvement. Equipped with a robust foundation in mathematical modeling, statistics, and advanced machine learning techniques, he excels at the intersection of data and strategic business planning. His creative application of data analytics and machine learning, combined with a strong background in finance and consulting, enables executives to make informed, strategic decisions. His work encompasses detecting patterns, building models, and extracting insights from large datasets, underpinning a full-cycle, data-driven approach to product development or business growth.

Rodrigo's rich portfolio of projects across various domains demonstrates his capability to apply cutting-edge machine learning and data science techniques to solve real-world challenges. Whether automating workflows, refining business strategies, or enhancing object detection accuracy, his contributions have consistently delivered tangible improvements and innovation.

work experience

Rodrigo Gonzalez is the Founder and Machine Learning Engineer at AI Consulting, where he engages with clients to identify AI and ML use cases and opportunities. By developing tailored AI solutions using frameworks like TensorFlow, PyTorch, and Scikit-Learn, Rodrigo enhances operational efficiency, informs strategic decision-making, and unlocks new avenues for growth and profitability.

Previously, he served as a Machine Learning Engineer at DataRobot from March 2019 to May 2022. During his tenure, he led significant projects such as the COVID HHS Product Time Series Predictive Modeling, where he steered a team to devise predictive models for COVID cases and deaths. This accelerated vaccine trials and the delivery of treatments. He also integrated advanced model algorithms into the DataRobot AutoML product, optimized preprocessing, and achieved a 20% boost in model performance.

Before DataRobot, Rodrigo worked at UTC Aerospace Systems (UTAS) as a data Scientist from May 2017 to January 2018. His work included architecting and deploying deep learning models for object recognition and detection in aerial imagery, leading to a significant accuracy boost. He also designed AI systems for image labeling and signal processing software, enhancing national security and operational efficiency.

Earlier in his career, he was a junior mergers & acquisitions associate at Beacon Hill Equity Group in Boston, MA. There, he engaged in diverse transactions, from initial client pitches to closing, communicated complex financial and strategic matters, marketed services, analyzed financial information, and managed contact and due diligence.


technical skills

  • Programming Languages: Proficient in Python, Scala, R, Bash, and SQL with experience in Golang, Lua, Typescript, Java, JavaScript, and node.js.

  • Machine Learning Frameworks & Libraries: Expertise in Pandas, NumPy, SciPy, PySpark, PyTest, Flask, PyTorch, TensorFlow, TensorBoard, Keras, Scikit-Learn, HuggingFace, WandB, XGBoost, LightGBM, CatBoost, spaCy, Hyperopt, LangChain, SentenceTransformers. Experience with Django, Apache Spark, Kafka, Kubernetes, CUDA, TensorRT, Intel HLS, LAPACK, BLAS, OpenMP, Open MPI, and LaTeX.

  • Data Science Skills: Proficient in Econometrics, Predictive Analysis, Quantitative Analysis, EDA, ETL, Feature Engineering, Cross-Validation & Model Evaluation, Data Modeling, Explanatory Analysis, Explainable AI, Time Series Analysis, Genetic Algorithms, and Signal Processing.

  • Machine Learning Techniques: Skilled in Frequentist & Bayesian Statistics, Regression & Classification, Regularization, Ensemble Methods, Neural Networks, Hidden Markov Models (HMMs), Anomaly Detection, Unsupervised Learning, Semi-Supervised Learning, Boosting, Natural Language Processing, Expertise in Generative NLP Models including BERT & Transformer models, Embedding Techniques, Language Representation Models, Image Recognition & Computer Vision, Computational Signal and Audio Processing, Reinforcement Learning, Transfer Learning, and Bayesian Hyperparameter Optimization.

  • DevOps, MLOps & Development Tools: Proficient in PyCharm, Docker, Kubernetes, Jenkins, Luigi, MLflow, JIRA, GitHub, and Git with a strong understanding of MLOps principles for efficient deployment, monitoring, and maintenance of machine learning models.

  • Cloud Platforms: Skilled in AWS and GCP.

  • Databases: Proficient in MongoDB, BigQuery, Athena, Postgres, SQL, DynamoDB, Cassandra, Redis, SQLServer, Amazon Redshift.

  • Data Visualization Tools: Skilled in Matplotlib and Seaborn with experience in D3.js, Gephi, and Tableau.

  • Operating Systems: Proficient in Linux Ubuntu and macOS with experience in RHEL and Linux CentOS.


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academic background

Rodrigo received a BA in Quantitative Economics and a BS in Chemical & Biological Engineering from the University of Colorado at Boulder in 2012, graduating magna cum laude. In 2015, he earned an MA in Finance from Harvard University. During his studies at Harvard, he founded Bloom Consulting (now AI Consulting LLC), where he spearheaded the creation of credit analysis algorithms using machine learning for small business lending platforms. He also managed technology and financial product development, economic and financial analysis, and the firm's strategic direction.

His academic pursuits include original tissue engineering, quantum mechanics, and econometrics research, encompassing investigations into biocompatible PEG hydrogels, computational quantum chemical analysis, and the cyclical characteristics of firm leverage through vector autoregression (VAR) modeling.

interests

- machine learning
- financial analysis & modeling
- advanced mathematics
- graph theory
- big data

- algorithms & data structures
- large scale software architecture
- mathematical programming
- combinatorics
- optimization