Join a team recognized for leadership, innovation and diversity We're looking for a new team member for our Global Finance analytics team who is motivated by cracking tough challenges with data, trained in problem solving, and with an unending thirst for learning. As a senior advanced data scientist, you will join a high-performing, global team, and be responsible for designing, developing, and implementing data driven solutions for all Honeywell business groups and functions. You will work closely with application architects to integrate results into operational platforms, including Hadoop and NoSQL architectures. You will also be responsible for recommending innovative solutions by using various data science methods including hypothesis testing, feature engineering, and also be responsible for defining the data acquisition strategy when required. This includes stakeholder management by presenting regular updates and final results to senior leadership of the customer organization. You will also be expected to actively participate in defining and governing our analytics strategy for Honeywell building out AI/ML capabilities of our Forge platform and promotingdata science methods and processes across functions. You will report to the Data Science Site Leader in the Honeywell Industrial Analytics organization, part of the Connected Enterprise.You must have: Master's degree in Computer Science, Engineering, Applied Mathematics or related field Exposure to Finance domain and use cases in larger global enterprise setting Minimum of 3-5 years of Data Science prototyping experience (Python and/or R tool-stack) using machine learning techniques and algorithms such as as k-means, k-NN, Na ve Bayes, SVM, Decision Trees Minimum of 3-5 years of Machine Learning experience of physical systems Minimum of 2-4 years of experience with distributed storage and compute tools (e.g. Hive and Spark) Minimum of 1-2 years of experience in deep learning frameworks like PyTorch, Keras Experience with designing, building models and deploying pipelines to production using containerized microservices and/or orchestrated batch runs We value: PhD degree in Computer Science, Engineering, Applied Mathematics or related field Experience with Natural Language Processing models Experience with Streaming Analytics (i.e. Spark Streaming) Experience with Recurrent Neural Network architectures Experience with Image Analytics Experience with SQL Experience with Tableau Experience working with remote and global teams Results driven with a positive can-do attitude
