Data Scientist

Summary

I am a skilled Data Scientist with expertise in machine learning, statistics, and data analysis. With proficiency in Python, SQL, and various ML frameworks, I have successfully applied models for protein disorder prediction and medical concept analysis. Experienced in cloud computing (AWS, Azure), I demonstrate strong analytical and problem-solving skills. With a background in Chemistry, including a Ph.D., and industry experience as a Quality Control Chemist, I bring a unique blend of technical and domain knowledge. With a total of 3+ years of experience, I am a proactive, creative thinker with leadership and communication abilities.

Expectations

I am excited about contributing my diverse skill set, including expertise in Data Science, to enhance team projects. I am eager to learn and grow, seeing this role as an opportunity for continuous development. I aim to actively contribute to achieving company goals. My collaborative nature and experience working in cross-functional teams position me well for fostering a positive team dynamic. I am adaptable and ready to take initiative in tackling challenges, ensuring both personal and company success.

Employment Preferences

Expected Base Salary

**,000 USD

Academic Degree

Experience

Skills

• Data Scientist
• Machine Learning
• Statistics
• Python
• SQL
• Data Analysis
• Tableau
• PowerBI
• Data Visualization
• Programming Languages
• RDBMS
• Numpy
• Pandas
• Scikit-learn
• Seaborn
• OpenCV
• Scipy
• Streamlit
• Matplotlib
• Pytorch
• Xgboost
• Pycaret
• Spacy
• Keras
• Tensorflow
• PyTorch
• Beautiful Soup
• PandasAI
• Gensim
• Rankbm25
• Fuzzywuzzy
• SQL RDBMS
• PostgreSQL
• MongoDB
• MySQL
• Duckdb
• Hadoop
• Spark
• ML
• Linear
• Logistic Regression
• Classification
• Predictive Modeling
• Regularization
• Support Vector Machines PCA
• K-means Clustering
• KNN
• Deep Learning
• Neural Networks
• ANN
• BNN
• NLP
• NLTK
• SpaCy
• Word2Vec
• TF-IDF
• Times Series Forecasting
• Decision Trees
• Ensemble Methods
• Random Forests
• AdaBoost
• Gradient Boosting
• Feature Selection
• Extraction
• Data
• Cleaning
• Wrangling
• Modeling
• Exploratory Data Analysis
• Power BI
• MS Excel
• Processing Large Data Sets
• Experimentation
• Distributed Computing
• PySpark
• Hypothesis Test
• A
• B Testing
• Statistical Analysis
• Cloud Computing
• Tools
• Amazon Web Services
• AWS
• [EC2
• S3
• Glue Catalog
• Glue DataBrew
• SageMaker]
• Docker
• Git
• Data Orchestration
• Mage AI
• Airflow
• Azure ML Studio
• Professional
• Leadership
• Analytical
• Creative Thinking
• Problem-Solving
• Communication
• Collaboration
• Presentation