Machine Learning Data Scientist

DENIS KOMEN

Email: **********@*****.***

Contact No: +1-646-***-****

PROFESSIONAL SUMMARY:

Hardworking Statistician and Data scientist with deep expertise in quantitative analysis. Offering strengths in assessing data reliability and eliminating errors. Highly adept in technical writing and process documentation. Logical Statistician committed to collecting and analyzing reliable, accurate data. Adept working with R, SAS, and machine learning. Known for strong communication skills and creating clear reports from complex information. Highly motivated employee with desire to take on new challenges. Strong work ethic, adaptability, and exceptional interpersonal skills. Adept at working effectively unsupervised and quickly mastering new skills. Hardworking employee with customer service, multitasking, and time management abilities. Devoted to giving every customer a positive and memorable experience. Ambitious, career-focused job seeker, anxious to obtain an entry-level Data science and statistics position to help launch a career while achieving company goals. Diligent College Student focused on Data science and statistics and dedication to prompt project completion and continual adaptation. Team-oriented collaborator with reliability and focus on equitable task distribution through group projects and motivation to accomplish mutually held goals. Work Experience:

Global Pro Ai (Dec 2023 – Present)

Position: Internship

Responsibilities:

Developed machine learning models and algorithms for predictive analytics.

Conducted data pre-processing operations such as feature engineering, normalization, and imputation.

Utilized various techniques, including linear regression, logistic regression, decision tree, random forest, gradient boosting, and neural networks.

Researched new methods of machine learning to stay up to date with industry trends.

Data visualization-Use data visualization software to present findings to stakeholders

Carrying out the preprocessing of structured and unstructured data

Enhancing data collection procedures to include all relevant information for developing analytic systems

Processing, cleansing, and validating the integrity of data to be used for analysis

Analyzing large amounts of information to find patterns and solutions

Developing prediction systems and machine learning algorithms

Presenting results in a clear manner

Propose solutions and strategies to tackle business challenges US Army Reserve (Part-Time)

The Medical operation Data system (MODS)

Duration: (Sep 2022 – Present)

Position: Data Analytics

Responsibilities:

Predictive Analytics and Preventive Care using Python, SAS and R to build a model to predict the risk of developing a condition. Example: Combat Casualty Care

Analyze patterns in injuries and outcomes to improve combat casualty care.

Mental Health and Resilience-Monitor and analyze mental health data to identify trends and risk factors.

Healthcare Delivery and Optimization -Use Electronic Health Records (EHR) data to improve diagnosis and treatment.

Create, document, organize, and cross-reference records and files.

Using the statistical analysis cell to perform comprehensive, strategic studies and short-term, ad-hoc analyses.

Complex analysis of training course questionnaire responses.

TUTOR

Kansas State University Student Success Center, Student Assistant (Sep 2022 – DEC 2022)

Responsibilities:

Tutored Mathematics and Statistics

Designed automated scripts to improve system performance and reduce manual tasks.

Prepared charts and diagrams to illustrate system operation results to staff in other departments.

Helped students with various programming languages such as R, SAS, and Python Education:

Kansas State University (2019-2024)

Bachelor of Science: Statistics & Data Science Manhattan, KS University of Nairobi

Bachelor of Science: COMPUTER SCIENCE

Certifications:

Base SAS 9.4 Certified by East Biost.

Clinical SAS

Skills:

Machine Learning

Strong Problem solving

Data Visualization

Proficient in SAS, Python, and R Programming languages.

Knowledgeable in Big Data technologies such as Jupiter, Spark, and NoSQL databases.

Teamwork and Collaboration

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