Our client is looking for a senior data scientist for our first-of-its-kind sales analytics platform, which combines a proprietary, active-learning network with applications that are ready to use, data backed, and built on predictive analyses.
Our ideal candidate will have a strong computational background (complimented by Statistics/Math/Algorithmic expertise), a healthy portfolio of dealing with Big Data, a passion for empirical research, a solid understanding of machine learning algorithms, and will absolutely love finding meaning in multiple imperfect, mixed, varied, and inconsistent data sets.
You must be a team player who will thrive in a collaborative environment, and you must be driven to create innovative, world-class products and get them to market.
Advanced degree in Applied Statistics, Economics, Computer Science, or Operations Research (Master’s degree required).
1+ years experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms including supervised and unsupervised learning, boosting and ensemble methods.
Ability to aggregate, normalize and process data by authoring predictive algorithms to synthesize and present actionable data insights.
Technical mastery in one or more of the following languages/tools to wrangle and understand data: Python (NumPy, SciPy, scikit-learn), R, Matlab, Spotfire, Tableau.
Experience with data manipulation and analysis using SQL, noSQL, Java, C, SAS, and machine learning suites such as Mahout, Weka, and RapidMiner.
Experience with cloud computing and Hadoop (MapReduce, PIG, HIVE)
Experience with third-party API integration.
Advanced degree in Applied Statistics, Economics, Computer Science, or Operations Research (Master’s degree required).
1+ years experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms including supervised and unsupervised learning, boosting and ensemble methods.
All your information will be kept confidential according to EEO guidelines.
Job details are sourced from the employer's original posting.
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