Machine Learning Engineer Resume San Bruno, CA - Hire IT People

SUMMARY

Providing the understanding the connection between machine learning models/algorithms and data analytics in an interdisciplinary engineering milieu and utilizing computational skills/methods to solve complex problems in scalable venues as a Data Scientist.
A results - driven, adaptable, and analytical professional with hands-on experience in coding in Python, Scala, R, Linux Shell Scripting, MATLAB and SQL.
Areas of expertise: machine learning & data mining, and inferential statistics to perform optimization
O bject Oriented Programming (OOP) and its broad range of application, mainly in Python
Big Data hands-on experiences, Hadoop Ecosystem, Pig, and Hive, mainly in Spark
Neural Network implementation, feedforward, backpropagation on Ecommerce projects
Programming: Python, R, Scala, Matlab, Linux shell scripting, and LaTEX
Statistics, uniform, binomial, Poisson, and normal distribution, A/B tests
NLP & recommender system integration
Data Analytics (Python in Numpy, Pandas, Matplotlib, Seaborn, etc), statistical analysis software (R), databases (SQL)
Machine Learning/algorithms in Python&R: Supervised/Unsupervised learning, Naive Bayes, Regression, Clustering of Scikit-learn
Deep Learning working knowledge

PROFESSIONAL EXPERIENCE

Confidential, San Bruno, CA

Machine Learning Engineer

Responsibilities:

Mining customer behavior data, like previous purchase history, to build personalized customer genomes; experimenting and implementing ML algorithms, ranging from Logistic regression to neural network
Building a recommendation engine by taking customer behavior data on both Python and Spark, MLlib environments.
Researching on search ranking, search relevance interpreted by graph algorithms, like PageRank, and implementing solutions on Pyspark GraphFrames under Hadoop Clusters.
Preprocessing various data sources, like POS, customer clicks, etc. by using SQL queries and manipulating/visualizing processed data for later model training/testing purposes w/ scikit learn Python API.

Confidential, Irvine, CA

Project Engineer/Data Analyst

Responsibilities:

Building predictive models for marketing/business response based on product previous sales data and extracting/engineering feature spaces from models to convert into actionable solutions.
Managing JIRA SQL account for development cycles, root causing design flaws of HW w/ corrective plans

Confidential, Tustin, CA

Data analyst

Responsibilities:

build predictive model for business intelligence; conduct rigorous statistical analysis

Confidential, Irvine CA

Statistical Data Analysis

Responsibilities:

Decode DNA sequences in gene RNR1: constructed kinetic models theoretically and computationally and developed a high throughout assay by SPR instrumentation experimentally in order to demystify the transcriptional regulation between transcription factors and DNA sequences in promoters of gene RNR1, which turned out to be a good predictive model to corresponding protein binding data.
Statistical Data Analytics: applied machine learning skills to develop a regression algorithm of supervised learning and analyzed the protein binding data by simulating the biological system for optimization qualitatively and quantitatively from both deterministic and probabilistic points of view.

Confidential, Irvine CA

Research Assistant

Responsibilities:

Developing models and algorithms for simulating and visualizing light propagation in biological tissues.
Numerical Simulation (Finite Element Method, FEM) || Bio- Confidential
Successfully established the mechanisms/ algorithms that provide highly efficient and reproducible delivery of biologically-relevant molecules to single cells at high throughput.