How we do Data Science
Our agile and robust team of data scientists, statisticians, and engineers understand data and have hands-on experience in building end-to-end machine learning and AI solutions to make things easier, faster, and more efficient. We follow agile data science framework to create and validate customized analytic solutions using Lean methods with regular touch points.
DiscoveryDefine the problem being solved and understand the unique requirements, analyze the data, and assess the future goals to make recommendations for tools, technology, architecture.
Prototype & IterateBuild a Minimum Viable Product (MVP) in short time and continuously improve the MVP by rapid iterations and automatically train the solution to become more efficient and enhance the quality of data insights.
Bias DetectionMonitor for bias before, during, and after modelling in the system and remove them using a mix of pre-processing, training, and post-processing methods including regularizer, surrogate models, fair machine learning models, or by calibrating the hyper parameters.
ProductionDeploy the trained data model into production and continuously improve it by retraining to unlock the predictive power of the model
KubeflowPutting a trained model in production without having a pipeline to continuously retrain the model is bound to make that model outdated as time progresses. Our engineers build a data science pipeline using Kubeflow to ensure the data pre-processing, parameter tuning, and model training steps are part of the CI/CD pipeline and can leverage the multi-step workflow model
Data PipelinesWhen it comes to transferring huge volumes of information quickly, powerful large-scale data processing is vital. Utilizing open source, lightning fast, reactive and distributed cluster computing frameworks (such as Spark, MapReduce, Hadoop, Hive, Kafka, Casandra, ElasticSearch, and Akka) we can create a data pipeline tailored to the specific needs of your project.
Machine LearningOur team has expertise in the algorithms and the math at the core of Machine Learning. Whether you're looking for object detection, predictive analysis, model trending, or bias detection, our team can work with small amounts of training data to prepare a model with high accuracy. Our focus on natural language processing (NLP), computer vision, and predictive analytics allow you to automate decision-making and pattern recognition processes trained from your data sets or ones carefully selected by us.
BioinformaticsOur expert team of bioinformaticians, statisticians, molecular biologists, computer scientists, and scientific programmers provide in-depth bioinformatics analysis to provide high-quality, publication-ready genomics and proteomics data. We are well versed in Next Generation Sequence data management and analysis, Genotyping and SNP data analysis, Microarray data analysis and tools, structural and functional genomics, and statistical and bio-mathematical modeling.