Data Scientist
Key Responsibilities
-
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
-
Select features, building and optimizing classifiers using machine learning techniques
-
Mine and analyze data from client databases to drive optimization and improvement of product development, marketing techniques and business strategies.
-
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
-
Processing, clean, and verifying the integrity of data used for analysis
-
Perform ad-hoc analysis and presenting results in a clear manner
Required Qualifications
-
Experience in one or more of the following programming languages: Python, R, MATLAB, Julia
-
Experience in exploratory data analysis
-
Experience in data visualization using one or more of the following packages/tools: seaborn, matplotlib, plotly, ggplot, Tableau
-
Knowledge of machine learning techniques and algorithms, such as K-nearest neighbors, naive bayes, support vector machines, random forest, logistic regression, etc.
-
Excellent understanding of machine learning concepts such as overfitting and underfitting, the difference between bias and variance, generalization capability of the prediction model to unseen data, feature engineering, etc.
-
Excellent written and verbal communication skills for coordinating across teams
-
A drive to learn and master new technologies and techniques
Bonus Points
-
Data engineering experience; e.g. SQL, Hadoop, Spark, cloud computing
-
Competitive programming experience (e.g. ACM, Topcoder, Code Forces, etc.)
-
Experience participating in machine learning competitions (e.g. Kaggle, Hacker Earth, etc.)
-
Strong statistics background
-
An up-to-date portfolio (on GitHub?) showing your experience in all of the above!