As a Senior Data Scientist, you will be responsible for:
- Contributing in development and deployment of applied, predictive and prescriptive analytics. Develop self-learning systems that can predict failures and autocorrect based on data
- Gathering analysing data, devising data science solutions for high-performance models in scalable code. Propose innovative algorithms and pursue patents where appropriate.
- Working with engineering teams to incorporate solutions and create intuitive UX stories. Partner with data engineers on data quality assessment, cleansing and analytics.
- Researching and evaluating emerging technology and market trends to assist in project development and operational support for multiple teams or complex scenarios.
- Contributing to the development of software and data delivery platforms that are service-oriented with reusable components across multiple teams.
- Creating reports and other artifacts to document your work and outcomes. Communicating methods, findings, and hypotheses with stakeholders.
Fuel your passion
To be successful in this role you will:
- Have a MS Degree in Computer Science or in STEM, Majors. 6+ years as data scientist and technical hands-on coding experience.
- Have experience in Machine Learning/AI techniques including Deep learning (RNN, CNN, GAN, etc), Support Vector Machines; Regularization Techniques; Boosting, Random Forests, Ensemble Methods, image/video/audio processing, Bayesian and time series modelling.
- Have experience in Parallel programming frameworks for GPUs, TPUs and developed containerized solutions (Docker/Mesos etc).
- Have good implementation experience with R, Python, Perl, Ruby, Scala, Apache Spark, Storm, SAS and ability to work with a variety of Deep learning frameworks including TensorFlow, Keras, Caffe, CNTK, etc
- Have hands-on skills in sourcing, manipulating and analysing large volumes of data including SQL and NoSQL databases
- Have proven experience in using well-established supervised and unsupervised machine learning methods for large industry-strength data analysis problems.
- Reviews, analyses and develops architectural requirements at domain level, aligning architectural requirements with software development strategy. Leads and facilitates the domains architecture governance process based on EAs governance structure.
