Zakarie Hashi

ZAKARIE HASHI Phone: +(517) 402 -0440 LinkedIn , Quora, Email:- Chicago, IL Innovative forward-thinking Applied data scientist/Statistician with demonstrated experience in using statistics, machine learning and advanced analytical tools such as R/Python and SQL in solving real world business applications. Collaborative, competitive and team player with proven track record in leveraging data streams and scripts to produce concepts, and recommendations in large projects. Creativity and experience in design thinking, product strategy, and passion for delivering product using industry's best practices. I bring with me the experience of working for multi-billion-dollar corporations -- getting to collaborate with diverse research and product teams to deliver commendable results. CORE COMPETENCIES Data science, Machine learning & Bigdata. Supply chain and network optimization Statistics and hypothesis testing A/B testing, Design of experiment Software engineering skills Python, R, SAS certified, SQL, Hive, Hadoop Power-BI, R-Shiny and Dashboard Creation Experience in Linux and Git. Cloud Computing (AWS, GCP) Project Management and Organizational skills EDUCATION Effective communication & key presenter Master’s in applied Statistics Western Michigan University Kalamazoo, MI, 2016 – 2018 Bachelor in Statistics Irbid University Irbid, Jordan, 2010 – 2014 PROFESSIONAL DEVELOPMENT AND CERTIFICATIONS • • • • • • • • • • • • • • • • • How Google does Machine Learning Launching into Machine Learning Intro to TensorFlow Feature Engineering Art and Science of Machine Learning Exploring and Preparing your Data with Big Query Creating New Big Query Datasets and Visualizing Insights Achieving Advanced Insights with Big Query Applying Machine Learning to your Data with GCP AI, Machine Learning, and Deep Learning What is Data Science? Introduction to Data Science in Python Python Data Structures Neural Networks and Deep Learning Bayesian Statistics: From Concept to Data Analysis Improving Deep Neural Networks AWS Fundamentals: Migrating to the Cloud Design and Interpretation of Clinical Trials Awards: Best Data Visualization Award, DataFest, Loyola University Chicago,2017 Deliver best data visualization application using SAS and R to analyze millions of datasets provided by Indeed, wining 1st place out of 12 competing teams. Affiliation Member of the American Statistical Association (ASA) and the Royal Statistical Association (RSS) INTERESTS Healthcare, Data Innovation, Data Strategy, product development, Technology, leadership, and artificial intelligence. CAREER CHRONOLOGY & ACCOMPLISHMENTS AbbVie Oct 2020 – Present Chicago, IL Senior Data Scientist Utilized statistics and data analytics to help business analytics team solve complex problems such as creating opportunities and consolidation on products, build tools and dashboards. Selected Accomplishments: • Consult with internal and external stakeholders to determine how best to apply statistical learning to support business objectives across AbbVie’s Supply Chain • Assessed the opportunity of consolidating L ABV and L AGN final mile shipments to various markets resulted in $24MM cost savings yearly. • Present and provide training on latest development on data science topics to business analysts across AbbVie. Abbott Dec 2019 – Oct 2020 Chicago, IL APPLIED STATISICIAN Utilized statistics, design of experiment and statistical quality control to support validation and verification of clinical trials. Selected Accomplishments: • Lead and support Covid-19 research statistical analysis on IgM and IgG studies. Resulted in grants emergency use authorization for fastest available molecular point-ofcare test for novel coronavirus from FDA. • Conducted PCR statistical analysis on Covid-19 research and submitted EUA to FDA. • Develop R packages for statistical automation. Helped Abbott’s ADD unit transition from SAS to R in 2020, resulted in saving > $300,000 for the company yearly. • Providing oversight of the overall development strategy and execution for statistical policies within Abbott’s ADD business unit. • Developing organizational competency to enable the use of best-in-class engineering and statistical techniques in product and process development. • Presenting statistical concepts to management, regulatory agencies and scientists. The Climate Corporation/Bayer Sep 2018 – Oct 2019 Saint Louis, MO Applied Statistician Utilized data science tools along with statistical modeling to understand, identify and communicate farming practices and field environment conditions that will increase yield potential and sustainably improve grower efficiency. Collaborated with scientists and engineers as subject matter expert on design, development and delivery of statistical analysis. Selected Accomplishments: • Leveraged +100 GB of complex big data sets from Amazon's AWS S3 database, consisting millions of seed trials, using SQL and R for to produce insights. • Increased processes efficiency 90% by writing R scripts to automate grower reports with detailed statistical results, insights, and recommendations. • Designed solutions for grower reporting documentations with detailed statistics, which resulted in 50% reduction of errors and time during project life cycle. • Developed quantitative, empirical, design of experiment and machine learning models to characterize and predict how products will respond across diverse environments. • Solved computational challenges of scaling complex statistical algorithms on big data with engineer partners, protocol leaders and data management. MPI Research/Charles River Labs May 2018 – Sep 2018 Kalamazoo, MI STATISTICAL SCIENTIST INTERN Collaborated with Research Scientist/Data engineers on experimental design and statistical analysis of clinical trials using various statistical methods, including generalized linear models and Dunn’s rest in R. Worked closely with clinical project leads, data manager and regulatory affairs to quantify clinical outcomes in a clear and concise manner. Selected Accomplishments: • Wrote reproducible results with high quality R/SAS codes to analyze complex studies. • Independently performed statistical analyses such as ANOVA, generalized linear model, mixed model, repeated measures ANOVA, Fisher’s exact test, exact MantelHaenszel, and survival analysis.