LINA SPOKAUSKAITE

**** ********** ***, ***** **, 104**-***-*** 3690 ac8fvy@r.postjobfree.com

Authorized to work in the US for any employer

Objective

Looking for a junior level position with opportunity to learn and grow. Interested in machine learning, predictive modeling, statistical analysis, programming.

Work Experience

Programmer (Dec 2018 - Present)

Part Time Consultant (April 2018 - Aug 2018)

Programming Intern (July 2017 - April 2018)

GCE Solutions Inc.

Work on the Innovations team as a programmer for a data and document anonymization software. Experience using R, R Shiny, SAS, Java, JavaScript, and HTML languages.

Biostatistician (April 2018 - Aug 2018)

Health Research Inc. (HRI) Roswell Park Division

Analyzed, interpreted and visualized high throughput biomedical data (machine learning, predictive modeling, survival analysis, bioinformatics tools); Maintained RNA-seq pipelines; Researched and presented findings in team meetings. Experience using R and Python languages.

Education

MA in Biostatistics (Jan 2018)

University at Buffalo, The State University of New York Buffalo, NY GPA - 3.75

Participated in NCI-CPTAC DREAM Proteogenomics Challenge with a team where we built a prediction model for high dimensional data.

Master’s Project: built predictive models to predict protein abundance from high-dimensional, highly correlated and weakly predictive RNA and DNA data using different machine learning methods and compared their performance. Bachelor of Statistics, Econometrics (June 2012)

Vilnius University Vilnius, Lithuania

Sang in the university choir, participated in university running competitions, participated as a team leader in the university orienteering competitions.

Programming/Technical Skills

• R, R Shiny, R Markdown

• SAS

• JavaScript

• Python (NumPy, Pandas)

• HTML

• Microsoft Word, Excel, Powerpoint

• GIT

• SQL

• Matlab

• Shell Scripting

• Linux environment

• Azure environment

Statistical Skills

• Regression: Linear, Logistic,PCR, PLS, etc.

• ANOVA analysis

• Survival analysis

• Times series analysis

• Categorical Data Analysis

• Classification

• Clustering: K-means, Self-Organizing Maps,

Hierarchical)

• Association Rules

• Probabilistic Graphical Models: Gaussian, Bayesian Networks, Page Rank

• Principal Component Analysis(PCA)

Personal Qualities

Curious and always interested in learning, able to learn new things fast, creative at problem solving, flexible, work well in a team.

Contact this candidate