IBM jobs - Data Scientist - IBM Garage

Introduction
IBM is continuously accelerating its digital transformations to help clients modernize their applications, address new markets and make investments in emerging opportunities through our hybrid cloud and AI strategy. Creating client dedicated garages are key to delivering rapid innovation and desired outcomes for our clients.
Our clients at IBM Garage leverage multidisciplinary Garage teams across Enterprise Design Thinking; Lean Start-up strategies; development, security and operations (DevSecOps) to create an entrepreneurial “fishbowl” to deliver outcomes faster than would otherwise be possible. If the thought of innovating at start-up speed with enterprise-scale excites you, IBM Garage is the right team for you!
As a Data Scientist in the IBM Garage team you will part of a cross-functional team that delivers a unique client co-creation experience to accelerate client transformation.

Your Role and Responsibilities
Who you are

• You are a key contributor to a pre-sales Garage team ,partnering with client to understand business problems and propose solutions.
• You demonstrate strong business acumen and ability to understand business problems, formulate hypotheses and test conclusions to influence solution design.

What you will do

• Contribute to co-creation of rapid proofs of concept and minimally viable solutions that demonstrate business value, leading to client investment in strategic solution .
• Translate business problems into leading-edge analytics solutions using consulting skills ,industry expertise and technical knowledge
• Deliver meaningful insights and predict emerging trends to inform business solution that optimize client value
• Apply Data Engineering techniques to gather ,prepare, cleanse and transform client data for analysis and AI automation ,including automating data pipelines

Required Technical and Professional Expertise

• Excellent understanding of machine learning and deep learning techniques and algorithms, such Deep CNNs, Optimizers, Feature Engineering, Transformers, etc.
• Experience handling large scale production datasets and understanding of related challenges and processes to address them
• Experience with common data science toolkits such as NumPy, scikit-learn, spaCy, Keras, PyTorch, etc. Excellence in at least one of these is highly desirable
• Experience with NoSQL databases, such as MongoDB, DnamoDB, Cloudant etc and understanding of basic data wrangling techniques
• Good to have academic training in a quantitative discipline and /or a specialized degree in data science or analytics .
• Possesses relevant industry and /or business domain knowledge such finance or healthcare .

Preferred Technical and Professional Expertise

• Demonstrated experience in applying user centric approach to design and create compelling prototypes that lead to transformative change for the client
• Knowledge of a variety of modern application of data science, including machine learning ,optimization ,neural networks and /or artificial intelligence that can be applied to solve client problems
• Deep understanding of statistical machine learning models with Python or R to propose innovative solution
• Expertise in the use of cloud based infrastructure to manage the volume and veracity of complex data streams .

• None