IBM Watson IoT
In December 2015, IBM announced the new Watson IoT Global Headquarters and our first ever Watson IoT Client Experience Center. The new headquarters, located in Munich, will 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 will also serve 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 will cultivate 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 out 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 many different industries such as Finance and Technology. You will find a unique place to work whilst enjoying an amazing view across the City and to the Alps.
Working for IBM is your opportunity to join a company where you can make the world work better - we are IBMers, and that's what we do. World-class learning opportunities, mentoring and a flexible work environment where you will find a wealth of opportunities within IBM to create the career you have always imagined. There are no limits to the opportunities we offer - from design to analytics, consulting to sales, and development to marketing. Join IBM and discover what you can make of this moment. You'll be proud to call yourself an IBMer.
We are looking for an IBM IoT Industry Lab - Data Scientist
The
Data Scientist 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 influence and many others. This team 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 creates, tests and validates hypotheses for business problems. You must be able to work with experts in a business area; possess knowledge of business strategy / execution and identify approaches to improve the accuracy and effectiveness of analytics models. You will understand and prepare 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. You will be able to 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.
You will be familiar with several data and big data tools and use them to 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. You will create visual presentations of analytics results and sometimes translate quantitative insights for a non-technical audience. You will also be working with target users to deploy analytics solutions.
In addition to broad and deep data and analytics skills, the Data Scientist has strong business acumen, coupled with the ability to communicate their findings to both business and IT leaders in a way that can influence how an organisation approaches business challenges and advise on / select the business problems which have the most value for the organisation.
Typical responsibilities within this role include:
Assessing and preparing documents for contribution to the corpus upon which NLP and machine learning engine is founded.
Designing and conducting training of advanced cognitive models (Watson).
Working with a variety of experts in Architecture, Development and other Industry areas.
Refining, analysing and structuring relevant data.
Creating visual presentations of analytics results.
Conduct undirected research and frame open-ended industry questions.
Required Skills:
5 Years experience in Data and Big Data tools and use them to model, design, develop and apply appropriate statistical and mathematical methods and techniques to prepare data for use in predictive and prescriptive modelling in order to solve business problems as well as to create repeatable, automated processes; proven experience with some of the following methodologies and tools listed below:
Algorithms (e.g. computational complexity, Computer Science theory)
Back- End Programming (e.g. Python / Java / Rails / Objective- C)
Bayesian / Monte-Carlo Statistics (e.g. MCMC, BUGS)
Big and Distributed Data (e.g. BigInsights, Hadoop, Map / Reduce, Spark)
Classical Statistics (e.g. general linear model, ANOVA)
Data Manipulation (e.g. regexes, SPSS, R, SAS, web scraping)
Front End Programming (e.g. Javascript, HTML, CSS)
Graphical Models (e.g. social networks, Bayes networks)
Machine Learning (e.g. decision trees, neural nets, SVM, clustering)
Math (e.g. linear algebra, real analysis, calculus)
Optimisation (e.g. linear, integer, convex, global, CPlex)
Science (e.g. experimental design, technical writing / publishing)
Simulation (e.g. discrete, agent-based, continuous)
Spatial Statistics (e.g. geographic covariates, GIS)
Structured Data (e.g. SQL, JSON, XML)
Surveys and Marketing (e.g. multinomial modeling)
Systems Administration (e.g. *nix, DBA, Cloud technologies)
Temporal Statistics (e.g. forecasting, time-series analysis)
Unstructured Data (e.g. NoSQL, text mining)
Visualisation (e.g. statistical graphics, mapping, web-based data-viz)
Experience with solutions and technologies within the following domains:
Internet Of Things
Sensor Technology
Business to Consumer / Business to Business / Business to Employee
Machine to Machine
Connected Appliance / Connected Person / Connected Home / Connected Building / Connected Vehicle / Connected Supply Chain
Predictive Maintenance
Industry 4.0
Fluent English
Intermediate German
-
Group ID: GBS
Job Family: Not Applicable