Senior Data Scientist

Job description a Data Scientist role, who will be responsible for guiding the successful delivery of Analytic Solutions to internal customers. The Data Scientist will be responsible for designing and executing processes related to AI, ML, predictive / analytical modeling, data mining, and research on large scale, complex data sets, using statistical, machine learning, graph modeling, text mining and other modern techniques. This individual is also responsible for collaborating with various teams and providing periodic updates through presentations and prototype demonstrations. The role will require working on multiple projects simultaneously. This position will also be involved in the formulation of key business requirements to be solved, rationalizing the various analytical approaches to solve those problems. Finally, this position is involved in helping to develop, analyze and draw conclusions, and presenting the results back to business users. Key responsibilities M ust know the in and out of the AI/ML algorithm being used and not just the library to call. Should have commissioned at least two projects end to end beyond the Proof of Concept. Design state of the art descriptive, diagnostic and predictive algorithms based on the business Requirements Deliver enterprise level analytics solutions to SLB customers Provide analytics solutions in Big data platform which can scale Design distributed, GPU and parallelized algorithms Architect the data science solutions to complex high dimensional data Deep dive on to theoretical and implementation details and provide the solution fundamentals Support architecture and platform team to optimize their operation Capable to train and gain expertise quickly on new Infrastructure tools and all assigned technologies Business Engage with the business segments and internal stakeholders to capture requirements Work closely with analysts and business process managers to develop an end-to-end analytics solution Present and Communicate solution design with Business & IT audience External Presence Engage with the external technical and business community to brand and differentiate analytics best practices in Participate in technical forums and other appropriate events and conferences Qualifications and Requirements Essential qualifications PhD or master’s degree in computer science, Electrical Engineering, Mathematics and Computing, Operations Research from top tier institutes. Devops driven 4-6 years of Industrial experience in developing core machine learning algorithms Academically trained in the field of machine learning/AI/Data Science/Computer Vision etc Excellent communication, verbal and written skills Key competencies in data science technologies Strong background in some of these listed areas: Machine learning, time series analysis / sensor processing, AI/Deep Learning, optimization/operations research, text analytics/NLP, Applied Mathematics, Decision Sciences, Computer Vision Building and applying machine learning / predictive modelling in real-world use cases Strong understanding and implementation and solution architecting of predictive / analytical modeling techniques, theories, principles, and practices Strong theoretical foundations in machine learning, optimization, stochastic process, linear algebra etc. Excellent knowledge of data mining / predictive modeling tools such as Python, Spark, Tensorflow, Keras, MLlib etc. Ability in designing distributed and parallelized algorithms Ability in deploying real world solutions in Hive, Spark and other Hadoop Technologies in Cloud and In-premise Capable of delivering on multiple competing priorities with little supervision Other skills and abilities Deep understanding of big data platforms such as Azure, Google cloud etc. Ability to abstract model representations and formulate repeatable models Strong ability to work in a fast-paced environment Strong ability to work both autonomously and in a team Strong ability to communicate complex quantitative analysis in a clear, precise, and actionable manner to both technical and non-technical audiences Understanding of Oil and Gas domain is a plus Experience working with, processing and managing large data sets (multi TB scale) is preferred Experience in real-time stream processing is a plus Keep continuously up to date on all assigned technologies