Client Technical Specialists (CTP) are the technical experts and advisors to clients, IBM sales teams and/or IBM Business Partners. As a CTP you understand the client's business requirements, technical requirements and/or competitive landscape. You apply your business insights, build and maintain client relationships, incorporate hardware, software and services into client-valued solutions and ensure client readiness for the implementation of technical solutions. This is an opportunity to shape the future for both IBM and its clients. Start your journey now!
Your Role and Responsibilities
As a Data Scientist working at the IBM Garage, you will be the Subject Matter Expert on Data and AI Statistical models and how they apply to business problems.
Led by a solution architect, you will advise on and help implement models in Machine Learning, Optimization, Neural Networks, and Artificial Intelligence such as Natural Language, and other quantitative approaches.
You will act as a key contributor partnering with clients to understand business problems and propose solutions.
You will deliver meaningful insights and predicts emerging trends to inform business solutions that optimize client value.
You will contribute to co-creation of rapid proofs of concept and minimally viable solutions that demonstrate business value, leading to client investment in strategic solutions.
To be successful in this role you:
- demonstrate strong business acumen and ability to understand business problems, formulate hypotheses and test conclusions to influence solution design
- are familiar with data science practices from working in code notebooks, building, validating models, and deploying models via APIs into applications or workflows, and monitoring & retaining models.
- are able to create machine learning pipelines and train models.
- are familiar with Data Engineering techniques (gather, prepare, cleanse, and transform client data for analysis and AI automation, including automating data pipelines)
- Leverage a variety of structured and unstructured data sources, analytics, AI tools, and programming languages to derive meaningful data insights (e.g., Python, R, Spark, TensorFlow, Jupyter, etc.)
- Possess relevant industry and/or business domain knowledge such as Finance or Health Care which you will apply to shape solutions
- Work in an Agile fashion, iterating on the solution to react to client feedback and demonstrate rapid progress
- Expand partnerships at all levels of the client organization to identify new opportunities for data science applications
Minimum Salary based on Austrian market ranges: EUR 34.580,- p.a. Overpayment is possible based on the candidate's education and experience.
Required Technical and Professional Expertise
- Graduate degree in computer science, statistics, information systems or another quantitative field
- At least 4 years experience in programming skills in Python, R, Scala or Java (preferred Python)
- At least 4 years as a Data Scientist with a deep understanding of Statistics and Probability
- At least 4 years of experience in the field of machine learning (data ingestion, feature engineering, modelling including ensemble methods, predicting, explaining, deploying and diagnosing over fitting)
- At least 3 years of experience in applying supervised, unsupervised and semi-supervised learning techniques
- At least 2 years of experience in deep learning and neural nets
- At least 2 years in a client facing role (communicating effective with line-of-business end users and being used to lead client discussions)
- Experienced with applications to visualize data using open source tools such as Shiny
- Fluent in German and English language
Preferred Technical and Professional Expertise
- Academic training in a quantitative discipline and/or a specialized degree in data science or analytics
- Understanding of Analytics Life Cycle and / or Crisp DM method and practices
- Experience with RESTful APIs
- Demonstrable experience in private and public Cloud
- Experience in developing and delivering appropriate analytic and/or machine learning models to achieve business goals
About Business UnitIBM has a global presence, operating in more than 175 countries with a broad-based geographic distribution of revenue. The company’s Global Markets organization is a strategic sales business unit that manages IBM’s global footprint, working closely with dedicated country-based operating units to serve clients locally. These country teams have client relationship managers who lead integrated teams of consultants, solution specialists and delivery professionals to enable clients’ growth and innovation. By complementing local expertise with global experience and digital capabilities, IBM builds deep and broad-based client relationships. This local management focus fosters speed in supporting clients, addressing new markets and making investments in emerging opportunities. Additionally, the Global Markets organization serves clients with expertise in their industry as well as through the products and services that IBM and partners supply. IBM is also expanding its reach to new and existing clients through digital marketplaces.
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