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What you'll do:
You will work with a team of highly technical and motivated developers.
Collaborate and work with teams spread across geographies and time zones.
You will work on the entire lifecycle of development projects, both customer specific and SAP-defined. This includes the analysis and specification of the customer-specific business requirements as well as the design, implementation, maintenance and in case of cloud services operation of customer-specific solutions.
Implement backlogs for functional and non-functional requirements.
Design, develop, deploy and monitor efficient AI/ML modules that drives complex business applications.
Adhere to SAP's agile engineering practices and processes. Own your code from ideation to development, across the full stack and through QA and support.
You will work on multiple topics and technologies with adequate enablement.
What you bring:
Master’s in a highly quantitative field (Machine Learning, Operational Research, Statistics, Mathematics, etc.) preferably from a reputable institution like IITs, IISc, or equivalent
4+ years of industry experience in a data scientist role
Solid understanding of the mathematics related to data science - probability, statistics, linear algebra etc.
Extensive knowledge of various machine learning algorithms and concepts used to build predictive models.
In-depth knowledge in at least 2 of the following data science domains:
Text Analysis and Natural Language Processing
Neural Networks and Deep Learning
Signal Processing, Image/Video processing and recognition
Reinforcement Learning
Hands on experience with computational packages (Numpy, Scipy, Pandas, Scikit-Learn, StatsModels, Keras, Tensorflow, etc.) and visualization tools
Highly proficient in SQL and good knowledge of relational database
Prior experience in deploying machine learning models into production
Experience in working with GPUs to develop models
Possess strong interpersonal and stakeholder management skills
Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
Strong written and verbal communication skills
Demonstrated the ability to independently develop new concepts and stay current with academic research
Exposure to SAP modules along with prior experience in cloud technologies like BTP, AWS, GCP, etc. is desired.
Publications or presentations in recognized Machine Learning and Data Mining journals/conferences
Identify and translate real world customer problems into feasible technical solutions and implement them independently.
Expectations and Tasks:
Conceptualize, design and deliver high quality solutions and insightful analysis
Work on gathering data and requirements, participate in solution scoping and architecture, research and prototyping innovative models
Build solutions by exploring data, building & validating models and deploying them to deliver maximum business impact
Interact with both - internal and external stakeholders on a daily basis
Handle multiple projects as an individual contributor and be a multiplier by actively mentoring other resources within the team
Be up-to-date with latest and best practices in delivering enterprise grade data science solutions
Build credibility and trust with customers and project teams during project execution
Demonstrate adaptability and flexibility to manage deadline pressure, ambiguity and change
Continually enhance existing skills and seek new areas for personal development.
Collaborate with product owner, architect, fellow developers, quality and user assistance specialists on design, architecture, hands-on coding, testing, etc. to deliver best solutions to our customers
Work on the latest technology and ensure on-time, high quality solutions
Embrace lean and agile software development principles
Perform high-level analysis of any new requirements/change requests to the solution from a technical standpoint
Analyze the impact of any new requirements on the existing solution
Work closely with other CIS Engineering team members, SAP Product Development teams, external partners and customer teams to ensure successful project completion
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