GE - Senior Data Scientist (14-20 yrs)
The Senior Data Scientist will work with the team to create state-of-the-art data and analytics driven solutions, developing and deploying cutting edge scalable algorithms, working across GE to drive business analytics to a new level of predictive analytics while leveraging big data tools and technologies.
You will enjoy working with one of the richest data sets in the world, cutting edge technology, and the ability to see your insights driving real business outcomes on a regular basis. The perfect candidate will have a background in related quantitative or technical field, will have experience working with large data sets, and will have experience in data-driven decision making. If you have led a data analytics team focused on delivering results, a self-starter, and have demonstrated success in using analytics to drive the growth and success of a business, this is the role for you.
- Apply your expertise in quantitative business analysis, data mining, and the presentation of data to see beyond the numbers and drive enterprise level outcomes.
- Architect, Lead and Develop high performance, distributed computing algorithms using Big Data technologies such as Hadoop, text mining, and other distributed environment technologies.
- Execute and evaluate appropriate analyses (cluster analysis, logistic/linear regression, collaborative filtering, etc.) given an array of tactical and strategic objectives.
- 14+ years of experience in solving analytical problems using quantitative approaches (or equivalent)
- Bachelors in Computer Science, Math, Physics, Applied Economics, Statistics or other technical field. Advanced degrees preferred.
- Proven leadership skills to provide guidance to data engineers and analysts with technical expertise, domain knowledge, business experience and statistical/ modeling techniques, focused on the big data space
- Competent programming aptitude with excellent computation and data text mining skills, with expertise in using R, SQL, Python
- Machine learning including Bayesian methods, reinforcement learning, Neural networks, Support vector machines, Hidden Markov Models, relevance vector machines, Probabilistic/ Evidential Reasoning
- Experience with large data sets and distributed computing (Hive/Hadoop)
- Expertise in applying data science techniques and tools is required.
- Proven ability to work within a climate of ambiguity.
- Outstanding communication and presentation skills a must.
- Demonstrated leadership competencies such as teamwork, creative problem solving, flexibility and willingness to challenge the status quo.
- Excellent relationship management, strong team building, and the ability to work across business units and functions within complex organizations.
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