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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

  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

  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