IBM Watson IoT
In February 2017 IBM celebrated the opening of the new Watson IoT Global Headquarters and our first ever Watson IoT Client Center. The new headquarters, located in Munich, bring together researchers, developers and consultants in a "campus" environment to drive collaborative innovation and deeper engagement with clients and partners from around the world. The center also serves as a lab for data scientists, engineers and programmers to build innovative solutions at the intersection of cognitive computing and the IoT. The IBM Munich Center cultivates the most vibrant global ecosystem of clients, startups, researchers and academics from every industry. Openly and collaboratively, all these partners will work together to make our clients’ visions a reality and even better yet pose new innovations they haven’t yet imagined.
Located in a modern and exciting location, the Highlight Towers in Parkstadt Schwabing nearby the English Garden, Olympic Park and the City Centre are easily accessible by public transportation and offer many local restaurants and retail offerings. It is close to the university campus of TUM in Garching representing one of the biggest research institutions and surrounded by numerous worldwide operating companies from different industries like Finance and Technology. You will find a unique place to work at while enjoying an amazing view across the city and to the alps.
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We are looking for an IBM IoT Industry Lab - Data Scientist
The Data Science is charged with design, implementation and delivery of analytic models used by the individual solutions as well as ensuring the overall integrity and accuracy of the offerings as a whole. IBM analytic models include neural networks, clustering, natural language processing, machine learning, support vector machines, Bayesian inference and many others.
The Industry Lab Data Scientist also works directly with IBM Research to productize “first of a kind” prototypes and with services teams to help them help our clients to understand and take action using analytics.
The data scientist works closely with our customers to identify issues and creates, tests and validates hypotheses for business problems, must be able to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organization. The candidate identifies approaches to improve the accuracy and effectiveness of analytics models, understands and prepares data for analysis by applying knowledge of data sources and how they are gathered, stored and retrieved as well as manipulating large volumes of data. Thoroughly clean and prune data to discard irrelevant information. Explore and examine data from a variety of angles to determine hidden weaknesses, trends and/or opportunities. Familiar with several data and big data tools and use them, model, design, develop and apply appropriate statistical and mathematical methods and techniques to prepare data for use in predictive and prescriptive modeling in order to solve business problems as well as to create repeatable, automated processes. Creates visual presentations of analytics results and sometimes translates quantitative insights for a non-technical audience. Works with target users to deploy analytics solution.
In addition to broad and deep data and analytics skills, the data scientist has strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge and advise on and select the business problems that have the most value for the organization.
Assumes additional responsibilities as assigned. Typical responsibilities include:
Assessing and preparing documents for contribution to the corpus upon which NLP and machine learning engine is founded
Designing & conducting training of advanced cognitive models (Watson)
Working with a variety of experts in architecture, development and the industry areas.
Refining, analyzing and structuring relevant data
Creating visual presentations of analytics results
Conduct undirected research and frame open-ended industry questions
Required Technical and Professional Expertise
2 years of Subject Matter Expert in one of the target industries (Automotive, Chemicals & Petroleum, Electronics, Government, Industrial Products, Insurance) with proficiency across the Industry Value Chain.
10 years of experience in several data & big data tools and use of them. Including:
Algorithms - computational complexity, Computer Science theory
Big and Distributed Data - BigInsights, Hadoop, Map/Reduce, Spark
Classical Statistics - general linear model, ANOVA
Graphical Models - social networks, Bayes networks
Machine Learning - neural nets, SVM, clustering
Natural Language Processing - linguistics
Spatial Statistics - geographic covariates, GIS
Temporal Statistics - forecasting, time-series analysis
5 years of experience delivering innovative solutions from concept through implementation in a complex environment while consistently meeting client expectations
Preferred Tech and Prof Experience
IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.