We are a startup looking for an experienced data scientist to help us with predictive modeling and classification.
We have "relatively" clean data (numerical mostly) and want to bring someone on as a contractor to help us build initial models. We would like all code to be written in Python.
Obviously strong proficiency in sci-kit learn, numpy, scipy and similar libraries is required. Familiarity with the practical usage and theory of statistics and probability as well as basic (supervised) machine learning algorithms (linear and logistic regression, decision trees, random forests, boosting, support vector machines, etc.) is needed. Knowledge of less interpretable algorithms such as neural nets is a plus but not a requirement. We are looking for interpretable models!
Knowledge of unsupervised algorithms for feature design and dimensionality reduction (clustering, PCA, NMF etc) would also be appreciated, as well as data visualization and knowledge of SQL and noSQL databases.
Skills needed:
python, data cleaning, prediction, classification, supervised machine learning, unsupervised machine learning, linear regression, logistic regression, boosting, random forests, support vector machines, data visualization
We are flexible with payments. We can work hourly or on a fixed price basis, depending on the experience and time and cost estimate of the freelancer. We are hoping to spend less than 500 dollars for the first set of models on the first data set, including a report or Jupyter notebook with graphs, interpretation and recommendations.
About the recuiterMember since Sep 5, 2017 Lucas Nguyen
from Queensland, Australia