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Statistics everywhere!
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Statistics everywhere!
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BNTechie/README.md

Data Scientist

Data Scientist (5+ years). PhD in Computational Physics.

Data Science Skills

• Programming Languages: Python, R

• Statistical Analysis: Generalized linear models, multivariate regression, time-series analysis.(scikit-learn, statsmodel, pandas, numpy)

• Machine Learning: Neural networks, support vector machines, random forests, boosting methods (scikit-learn, pyTorch, keras)

• Data Integration and Management: SQL, handling multi-omic datasets (genomics, proteomics, transcriptomic)

• Data Visualization: ggplot2, Matplotlib, Seaborn

• Big Data and High-Performance Computing: Use of HPC clusters for large-scale data analysis

• Bioinformatics Tools: Bioconductor, Galaxy

• Natural Language Processing: Text mining, Sentiment analysis, Topic Modelling (NLTK, SPacy, BERT)

Analytical Skills

• Data preprocessing, normalization, and transformation

• Predictive modeling and algorithm development

• Network and pathway analysis, Differential gene expression analysis

Research and Project Experience

• Developed and implemented predictive models for clinical trial data analysis, improving early-phase trial insights.

• Conducted exploratory data analysis and visualized complex datasets to identify trends and patterns.

• Designed and executed experiments to test hypotheses and validate models.

Soft Skills

• Excellent written and verbal communication skills in English

• Collaboration in interdisciplinary and multicultural teams

• Independent project management and leadership

Additional Skills

• Linux systems, command-line tools

• Version control (Git)

• Deep learning frameworks (TensorFlow, Keras, PyTorch)

• Experience with relational databases and big data technologies

Pinned Loading

  1. Regression_analysis Regression_analysis Public

    house price prediction, Comparison of Ml algorithm, Logistic regression, Multicollinearity, Multivariate regression analysis, Linear model with random effects, Robust regression

    Jupyter Notebook 1

  2. Bioinformatics Bioinformatics Public

    Differential Expression Analysis of protein, Gene set enrichment analysis, Multi-omic factor analysis, Pathway analysis, WGCNA

    Jupyter Notebook 1

  3. Data-preprocessing Data-preprocessing Public

    Creating empty dataframe, data normalization, Dimensionality reduction, Outlier detection, Overfitting of model and its solution, Remove column with zero values, Replace NA with zeros.

    Jupyter Notebook 1

  4. Exploratory-data-analysis-EDA- Exploratory-data-analysis-EDA- Public

    Exploratory Data Analysis on Black Friday sales dataset, 911 call data analysis, Chicago crime data analysis

    Jupyter Notebook

  5. Predictive-modeling Predictive-modeling Public

    Credit card fraud detection, Breast cancer prediction, Wine quality prediction, Bank note authentication, prediction of attrition of employees, Stock prediction, etc

    Jupyter Notebook

  6. Statistical-tests Statistical-tests Public

    Permutational Multivariate Analysis of Variance, Causal mediation analysis, PCA, adjusted p_values, correlation amon distance matrix, power analysis, exat t_test, Fourier transform

    Jupyter Notebook 1