Adesoba Adewale Olamide

DataOps Engineer

NabuMinds•  October 2022 - Present

• Communicate and collaborate with various teams to design, implement, and maintain data pipeline tooling, developing best practices for data collection, ingestion, transformation, and storage to access data needs and prioritize accordingly. • Automate serverless cloud solution deployment processes using the bitbucket pipeline for various data integration solutions. • Regularly reviewing cloud/data platform configurations and controls for data access, data security, data sensitivity, and data confidentiality • Build, configure, orchestrate, and manage airflow infrastructure via Google Kubernetes Engine while taking into consideration fault-tolerant and highly available solutions with CI/CD best practices. • Managed and administered the various networking resources tied to both our data and cloud solutions with highly secured best practices. • Maintain awareness and make recommendations regarding marketplace changes regarding our analytic systems. • Monitor and improve the performance, efficiency, effectiveness, and orchestration of our analytics systems across the cloud/data ecosystem. • Monitor system performance, troubleshoot issues, and implement solutions to mitigate data-related problems. • Document system architecture, processes, and best practices for knowledge sharing and future reference. • Implement and enforce security protocols, encryption standards, and access controls to protect sensitive data in the cloud environment. • Administer and provision identity and access management of the Snowflake ecosystem using Terraform.

Data Engineer

SendMe•  February 2022 - September 2022

Experience building distributed high-performance systems using Spark and Scala Experience developing Scala applications for loading/streaming data into NoSQL databases (MongoDB) and HDFS. • Designed Distributed algorithms for identifying trends in data and processing them effectively. • Experience in developing machine learning code using spark MLLIB Used Spark SQL for data pre-processing, cleaning and joining very large data sets. • Experience in creating data lake using spark which is used for downstream applications Designed and Developed Scala workflows for data pull from cloud-based systems and applying transformations on it. • Database migrations from Traditional Data Warehouses to Spark Clusters. • Setting up infrastructure on GCP with Terraform • Deployment of various data transformation code in dbt: local development vs production • Loading data to big query & PG-- using Airflow operator. • Connecting data studio for visualization with our big query

Data Scientist (Analyst)

IQUBE LAB •  January 2021 - February 2022

• Worked with SQL and Python to clean the data and perform Exploratory Data Analysis and feature engineering to inform the development of statistical models and improve model performance and flexibility in US hospital data. • Assist with the development of standardized reporting Excel sheets that align metrics and drivers with the associated hospital groups and characteristics. • Analyzed data with standard statistical methods, interpreting the results and reporting recommendations that can be implemented in model development. • Provided analysis using mathematical modeling tools to improve health care management and decisions in the health sector

Data SCIENTIST / Machine learning Engineer - Insights and Analytic

VICTEMIGE TECHNOLOGIES•  January 2018 - January 2019

• Build Functions, Procedures and Packages using Python/SQL • Use Microsoft Power BI for reporting dashboard. • Used panda’s library for data transformation and manipulation. • Data mining, wrangling, segmentation, modelling for generating varieties of reports using RDBMS. • High level use of Python programming for Machine Learning Models. • Queried databases and joined tables from multiple data sources (SQL Data bases, NoSQL Databases, csv and json files). • Provisioning stored data into a form that can be used by front-end analytics application. • Implementation of various machine learning algorithms in supervised and unsupervised learning Knowledge of Natural Language

Data Scientist/Research Analyst

NNPC RESEARCH AND DEVELOPMENT DIVISION•  January 2015 - January 2016

• Interpret data, analyze results using the appropriate statistical technique(s) and provide recommendation(s). • Worked closely with the manager exploration and production department as research assistant. • Identify, analyze, and interpret trends or patterns in simple and complex datasets. • Acquiring data from primary sources to aid Geo-Statistical project and better decision making for the organization. • Writing report(s) base on the findings from the analyzed data for either the organization or Geo-Statistical project.

WorldQuant University

Applied Data Science, Honors in Applied Data Science and Statistical Computing•  March 2021 - September 2021

• Relevant course work: Advanced Data Analysis, Data Wrangling, Object-Oriented Programming, Pandas, SQL, Python Data structures, loops • Project 1: Used basic Python data structures, functions, and control program flow to answer posed questions over medical data from the British NHS on prescription drugs. I had to use fundamental data wrangling techniques such as joining data sets together, splitting data into groups, and aggregating data into summary statistics. • Project 2: Used the Python package pandas to perform data analysis on a prescription drug data set from the British NHS. I answered questions such as identifying what medical practices prescribe opioids at a usually high rate and what practices are prescribing substantially more rare drugs compared to the rest of the medical practices. I used statistical concepts like z-score to help identify the aforementioned practices.

WorldQuant University

Applied Data Science, Honors in Machine Learning & Statistical Analysis •  March 2021 - September 2021

• Relevant course work: Anomaly Detection, Clustering, Decision Trees, Dimensionality Reduction, Gradient Boosting Trees, Linear Regression, Logistic Regression, Machine, Model Tuning, Natural Language Processing, Random Forest, Support, Time Series Analysis, Unsupervised Learning. • Project 1: Worked with nursing home inspection data from the United States, predicting which providers may be fined and for how much. I used the scikit-learn Python package to construct progressively more complicated machine learning models. I had to impute missing values, apply feature engineering, and encode categorical data. • Project 2: Used natural language processing to train various machine learning models to predict an Amazon review rating based on the text of the review. Further, I used one of the trained models to gain insight into the reviews, identifying words that are highly polar. With these highly polar words identified, one can understand what words highly influence the model's prediction.

University of Ibadan

Petroleum Engineering, BS•  January 2016 - January 2019

• Relevant course work: Statistics for Physical Sciences and Engineering, Computer Programming, Technical Writing and Presentation Petroleum Economics, Algebra, Drilling, Petroleum Production, Reservoir Engineering, and Modeling • Award 1: Petroleum Trust Development Fund (PTDF) Scholarship 2017 Award for exceptional students in engineering nationwide. • Award 2: Dean of the Faculty of Technology, University of Ibadan, Recognition for excellence, 2018.