Job Description

Software : AnyLogic, STELLA, Arena Programming : Python, Java Data Processing Tools : Python (Numpy, Pandas, etc.), Spark, cloud-based solutions such as GCP DataFlow; Machine Learning Libraries : Python (scikit-learn, pysim, etc.), TensorFlow, Keras, PyTorch, Spark MLlib; Code collaboration : git, github Independently working on building simulation models using object oriented approaches. Experience with agent based modeling, system dynamics modeling, discrete event modeling Experience with Systems Thinking concepts and application is a big plus. Demonstrated ability to create end-to-end technology prototypes and/or machine learning models for a given business use case or application. Demonstrated experience with rapid prototyping, using agile approaches to quickly test new ideas and fail fast . Demonstrated ability to apply a business framing to emerging technology solutions and communicate to business audiences in written and verbal formats. Demonstrated interest in emerging technologies such as Artificial Intelligence, Blockchain, Internet of Things, Virtual Reality, Augmented Reality, and Robotics. Demonstrating proven delivery within a number of large scale projects Demonstrating ownership of architecture solutions and managing change Understanding business development such as client relationship management and leading and contributing to client proposals Communicating project findings orally and visually, to both technical and executive audiences Developing people through effectively supervising, coaching, and mentoring staff Demonstrated contributions in firm development and knowledge building activities such as recruitment, intellectual capital development, staffing, marketing, branding Leading, training, and working with other data scientists in designing effective analytical approaches taking into consideration performance and scalability to large datasets Experience in innovation or lab environments is a plus. Excellent communication skills Role and Responsibilities: Leadership: Leading initiatives aligned with the growth of the team and of the firm Providing strategic thinking, solutions and roadmaps while driving architectural recommendation Interacting and collaborating with other teams to increase synergy and open new avenues of development Supervising and mentoring the resources on projects Managing communication and project delivery among the involved teams Handling team operations activities Quickly explore new analytical technologies and evaluate their technical and commercial viability Work in sprint cycles to develop proof-of-concepts and prototype models that can be demoed and explained to data scientists, internal stakeholders, and clients Quickly test and reject hypotheses around data processing and machine learning model building Experiment, fail quickly, and recognize when you need assistance vs. when you conclude that a technology is not suitable for the task Build machine learning pipelines that ingest, clean data, and make predictions Develop, deploy and manage production pipeline of ML and simulation models; automate the deployment pipeline Stay abreast of new AI research from leading labs by reading papers and experimenting with code Develop innovative solutions and perspectives on AI that can be published in academic journals/arXiv and shared with clients

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