Data Scientist

Summary

Data Engineer, Analyst and aspiring Data Scientist with extensive experience working within multiple technical tools and languages related to Python data science, Data Analysis, Engineering and building data pipelines, data ingestion, data munging/cleansing and building data models in large data environments, serving scientific users and consumers. Self-motivated and driven to learn and improve, completed coursework and certifications in: Python, Pandas, Data Visualization, Natural Language Processing (NLP), and Decision Science. Master of Computer Science, with emphasis in Data Science, and 3+ years experience working in the industry, with prior experience as systems engineer.

Expectations

Role must be a good fit
Good team and growth environment
Good opportunities

Employment Preferences

Expected Base Salary

**5,000 USD

Expected Hourly Rate

** USD/hr

Academic Degree

Experience

Skills

• Languages
• Python
• R
• C
• SQL
• Big Query
• Cloud Technology
• AWS
• GCP
• Data Engineering Tech Stack
• Vertica
• Looker
• ETL Tools
• Kettle
• Manual Scripts Executing As DAGs In Airflow
• Data Science Tools
• Anaconda
• Jupyter Notebook
• Google Colab
• GitHub
• Packages
• Keras
• TensorFlow
• Pandas
• NumPy
• Scikit-learn
• SciPy
• Matplotlib
• Google Trends
• PyTrends
• Seaborn
• Ggplot
• Framework
• Django
• GPU
• NVIDIA Quadro P6000
• Titan RTX On A Linux
• Proficient Knowledge On Machine Learning
• Regression
• Classification
• Perceptrons
• Gradient Descent
• Neural Networks
• Backpropagation
• VC
• Dimension
• Model Overfitting
• Proficient Knowledge On Data Mining
• Maximum Likelihood Estimation
• Bayesian Classification To Classify Words In NLP
• Bayesian Classification
• Bayesian Belief Networks
• Decision Trees
• Bagging
• Boosting
• Feature Engineering
• Dimensionality Reduction
• Clustering Techniques Like K-NN Classification
• K-means
• DBSCAN
• Apriori Principle.
• Kaggle Enthusiast
• Currently Enrolled In Code Competition LLM Prompt Recovery