If you are eager to use your creativity and results-oriented critical thinking to meet complex challenges and develop new strategies in the development of AI/Data-enabled propositions, then look no further … we would like to powwow with you. We're looking for a highly motivated individual with passion to drive the next generation in technology, including conversational and voice interfaces, recommender systems, NLP, Sentiment analysis, Computer vision, a.o., to build and lead a team of AI and Data Science architects, engineers and specialists.
To build our next generation smarts, you will be working with experts in a variety of fields, including clinical & regulatory specialists, UX designers, dental and skin care professionals, system architects, product management, as well as with heads of other organizations globally and with senior executives to integrate new technologies and refine system performance. You will help build learning systems, leveraging data sets consisting of user interactions and actions, collected from hundreds of thousands of consumer devices, per day to model, analyze, and predict user behaviors. While some of our algorithms run on resource constrained devices, others require large clusters on our cloud infrastructure. The AI/Data Science Leader will be responsible for understanding business entities and their relationships and representation in the Healthcare Platforms, Products, Services, and Tools. He/she will be a thought leader with a penchant for strategy and disciplined execution. This is a critical, highly visible, and strategic leadership role within the Personal Health cluster and within Philips Innovation Campus-Bangalore, that has the potential to drive significant business impact.
As the hands-on AI/Data Science leader, you will be responsible for guiding agile software development teams and managing projects from the conceptual stages through the development cycle. You will ensure that the development processes, architecture and standards are followed. You will also be responsible for the team's code quality, delivery schedule, and financials. The is a leadership role requiring deep understanding of the ML/AI software stack, people management skills and helping with their professional development.
- MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
- Total work experience of 15+ years with solid exposure to AI/NLP, Machine Learning/Deep Learning, data-driven statistical analysis & modelling solutions to consumer health/professional health domains. Last 3 years’ experience in leading and mentoring teams.
- Strong Knowledge of emerging technologies such as AI, Machine Learning, Deep Learning, Data Science, NLP, Computer Vision, Internet of Things (IoT) and hands-on experience with structured/unstructured data/text/image based descriptive/predictive analytics.
- Practical experience with machine learning algorithms such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests; experience with PostgreSQL, data models, XML, etc; experience with ETL tools and techniques, such as tools like Talend, Mapforce, map transformation and flow of data from a source to a target system and with visualization tools such as QlikView, Tableau, etc.
- Strong, proven programming skills in Python, C/C++, Java, R , MATLAB, Scala, and with machine learning and deep learning and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop, Kafka, Hive, Oozie, Map Reduce, Cassandra etc. Hands on experience in AWS technologies like AWS S3, RedShift, Glue, Lambda, EMR & Athena. Experience with writing complex programs and implementing custom algorithms in these and other environments.
- Experience in an applied R&D environment, working in an agile set-up to bring technologies to fruition, from initial concept to implementation
- Experience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks.
- Excellent communication skills (oral and written) to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to lead and work in a diverse team
- Experience in data management, data analytics middleware, open source frameworks and workbenches, platforms and infrastructure, cloud and fogging is a plus
Data Science, AI, ML, NLP, IOT
- Brainstorm with Business R&D and Product Management to identify innovations in AI/NLP/ML to help develop analytics workflows, predictive insights, user interaction technologies and capabilities while co-creating/influencing product roadmaps.
- Implement and prototype new algorithms and write code for novel AI/NLP/ML solutions. Develop strong AI / ML and emerging technologies skills in the team to build solutions that can be productized and launched in the market
- Investigate emerging AI/NLP and Data Science solutions and be conversant with latest developments in these fields
- Explain complex models to non-experts, in layperson terminology to stakeholders and managers, while also being able to discuss intricacies of complex algorithms with experts in the field
- Determine tradeoffs between internal technical implementation vs. partnerships with external teams/organizations/vendors for new technology-based solutions and capabilities
- Be at the forefront of development team's technical acumen and of self and while enabling upskilling of other team members to leverage ML / AI technologies
- Proactively build thought leadership for the organization by filing patent, writing white papers and participating/presenting in global conferences
- Drive industry best practices around data and metadata management, data quality, data governance, and data privacy. Ensure compliance with internal as well as external bodies.
- Define and maintain standards, methodologies for effectively capture, organize, integrate, maintain and orchestrate data. Develop, operate and drive scalable and resilient data platform to address the business requirements. Determine the ones that should be incorporated onto data architectures, and develop implementation timelines and milestones.
- Collaborate with data architect to develop architectural strategies for data modeling, design and implementation to meet stated requirements for metadata management, data warehouses and Extract Transform Load (ETL) environments.
- Responsible for driving harmonization and modular design of information, being processed within assets (i.e., product, system, software, service, platform, solution), in all parts of the business organization, compliant with the information-related parts of the HealthSuite Reference Architecture (HSRA), while leveraging (where appropriate) Philips common information models (per the HSRA Manifesto) and common information processing technology choices.
- Manage budgets, schedule, scope and quality. Define, agree and adhere with stakeholders on the key KPIs. Create visibility through effective communication, performance dashboards, reporting etc.