ayroui ayroui

A ML enthusiast by day, a PhD student by noon and a investor by night. I am more than what meets the eye. To know more, keep scrolling!

Worked with these organizations

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Degrees

Education

Live as if you were to die tomorrow. Learn as if you were to live forever. — Mahatma Gandhi

Auburn University, Alabama

Ph.D in Computer Science
(2020 - Present)


University of Illinois, Springfield IL

MS in Computer Science
(Jan 2016 - May 2017)


SIT, Pune, India

B.Tech in Computer Science
(July 2011 - May 2015)


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Roadmap

Work Experience

The only source of knowledge is experience. — Albert Einstein

VNS Health, New York
Senior ML Engineer

(Dec'22 - Present)

  • Designs and implements scalable and reliable machine learning (ML) systems used to develop, test, and deploy machine learning models.
  • Leverages technologies and platforms to support reproducible feature engineering and optimized machine learning model deployment at scale.
  • Creates robust monitoring solutions to understand model performance and manage model life cycles via a centralized model registry.
  • Partners with data scientists and IT data engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions.
  • Ensures data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, and transformation.
  • Identifies gaps and evaluates relevant tools and cloud computing technologies as needed to improve machine learning processes and build effective solutions.

  • Technology Stack: Python, Airflow, Snowflake, Amazon AWS, SQL, Docker.

    Technology Stack: Python, Airflow, Snowflake, Amazon AWS, SQL, Docker.

EvolutionIQ, New York
Senior ML Engineer

(October'22 - Dec'22)

  • Build ML models for production use.
  • Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies.
  • Suggest and implement new features to improve model performance and business logic.
  • Write and review production-quality PRs daily.
  • Translate client business problems into ML problems.
  • Build scalable machine learning models for claim time series forecasting and NLP text understanding.
  • Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets.

  • Technology Stack: Python, Tensorflow, PyTorch, Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes.

    Technology Stack: Python, Tensorflow, PyTorch, Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes.

AT&T, New York
Senior Data Scientist

(June'22 - October'22)

  • Working hand-in-hand with our industry partner on the cutting edge of the intersection of databases, knowledge graphs, and artificial intelligence.
  • Contribute to the development of a product for solving real-world, large-scale problems using knowledge graph technology.
  • Design and development of artificial intelligence and machine learning applications built upon the knowledge graph technology.

  • Technology Stack: Python, Azure Databricks, Pyspark, Palantir, REL, Julia, SQL.

    Technology Stack: Python, Azure Databricks, Pyspark, Palantir, REL, Julia, SQL.

Children's Hospital of Philadelphia
Applied Data Scientist II

(June'20 - June'22)

  • Applying natural language processing methods to clinical text to extract structured information.
  • Using the latest deep learning techniques to classify imaging studies.
  • Applying statistical models (with a focus on Bayesian methods) to assist researchers in analyzing missing, erroneous, or incomplete patient data.
  • Implement statistical and machine learning models, large-scale, cloa3Y data processing pipelines, and off the shelf solutions for test and evaluation; interpret data to assess algorithm performance.
  • Develop novel ways to apply published machine learning models to imperfect clinical data including the development of training datasets.
  • Develop high-quality, secure code implementing models and algorithms as application programming interfaces or other service-oriented software implementations.
  • Manage and scale applications using container technology and cloa3Z managed services.

  • Technology Stack: Python, Apache Spark, BigQuery, Kubernetes, Argo, Dataflow, Apache Beam, Terraform, Docker, R.

    Technology Stack: Python, Apache Spark, BigQuery, Kubernetes, Argo, Dataflow, Apache Beam, Terraform, Docker, R.

VNS Health, New York
Data Scientist

(February'19 - June'20)

  • Develop, build, test and deploy machine learning algorithms to support development of business processes for healthcare organization and subsidiary health plan provider, to improve business outcomes and quality of care.
  • Create and maintain framework for deploying machine learning algorithms using APIs.
  • Utilize resulting applications to implement, track and monitor predictive models used to guide business decisions.
  • Engineer computational solutions and develop algorithms and applications to meet the predictive needs of clinical and business units across the Visiting Nurse Service of New York.
  • Identify clusters of sub-populations of patients who may benefit from targeted care-management strategies: improves positive predicted value for patient outcomes based on sub-modeling for each cluster.
  • Ensure accuracy of deployed algorithms is monitored on an ongoing basis; alert management when algorithm performance declines, identify causes.
  • Ensure data quality throughout all stages of acquisition and processing, including sourcing, collection, ground truth generation, normalization & transformation.

  • Technology Stack: R, SQL, Python, Random Forest, XGBoost, Light GBM, Regression, Clustering, KNN, GBM, PCA, SVD.

    Technology Stack: R, SQL, Python, Random Forest, XGBoost, Light GBM, Regression, Clustering, KNN, GBM, PCA, SVD.

Jvion
Data Scientist

(June'17 - Jan'19)

  • Design statistical models/programs using R/Python to successfully test hypotheses and answer targeted questions in healthcare outcomes research.
  • Design algorithms for the recommended actions/interventions that will best prevent adverse events and deterioration.
  • Cluster analysis for identifying sub-populations of complex patients who may benefit from targeted care management strategies and improvising positive predicted value for patient outcome by sub-modelling on each cluster.
  • Perform analysis on the targets including hospital readmission among Acute Myocardial Infarction (AMI) patients, IP visits, ER visits, MRSA among diabetes patients, congestive heart failure,Clostridium difficile (C. diff.), pressure injury,sepsis and fall-injury.
  • Writing complex SQL queries for data investigation and mapping to extract data for analysis.
  • Build algorithms to reduce predictive analytics in driving population-level insights and the expected ROI from predictive population health analytic solutions.
  • Report and visualize results of statistical analyses, in the form of graphs, charts, and tables using Tableau.

  • Technology Stack: R, SQL, Python, Apache Spark, Tableau, H2O, Random Forest, XGBoost, HDBSCAN Clustering, KNN, GBM, PCA, SVD.

    Technology Stack: R, SQL, Python, Apache Spark, Tableau, H2O, Random Forest, XGBoost, HDBSCAN Clustering, KNN, GBM, PCA, SVD.

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Testimonials

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Life is 10% what happens to you and 90% how you react to it. — Charles R. Swindoll

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Developed by Rushabh Patel

Developed by Rushabh Patel

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