Eugene Mutai

Eugene s.mutai  Tel:-  email:- Results-driven data scientist with 6 years of experience in leveraging data analytics to drive business insights and inform decision-making. Skilled in machine learning, statistical analysis, and data visualization. Proven track record of developing predictive models and delivering actionable recommendations. Passionate about applying advanced analytics to solve complex problems and optimize processes.  Skills: Programming Languages: Python, R, SQL Machine Learning: Supervised and Unsupervised Learning, Regression, Classification, Clustering Data Analysis: Pandas, NumPy, Scikit-learn Data Visualization: Matplotlib, Seaborn, Plotly Big Data Technologies: Spark, Hadoop Deep Learning: TensorFlow, Keras Statistical Analysis: Hypothesis Testing, Time Series Analysis Tools: Jupyter Notebook, Git, Docker Database Management: SQL, MongoDB    Experience: Data Scientist   Developed machine learning models to predict customer churn, resulting in a 15% reduction in churn rate. Conducted exploratory data analysis on large datasets to identify key trends and insights, leading to improved marketing strategies. Collaborated with cross-functional teams to deploy data-driven solutions and drive business impact. Presented findings and recommendations to stakeholders, including executives, clearly and concisely. Data Analyst Intern   Assisted in data cleaning, preprocessing, and visualization for marketing campaign analysis. Conducted statistical analysis to evaluate the effectiveness of different marketing channels. Contributed to the development of dashboards and reports for tracking key performance metrics.    Projects: Predictive Maintenance System Developed a predictive maintenance system using machine learning algorithms to anticipate equipment failures and minimize downtime. Utilized sensor data to train predictive models for early fault detection and condition monitoring. Achieved a 20% improvement in maintenance efficiency and cost savings. Sentiment Analysis of Customer Reviews Conducted sentiment analysis on customer reviews using natural language processing techniques. Built a classification model to categorize reviews into positive, negative, and neutral sentiments. Provided actionable insights to improve product features and customer satisfaction.