Data Science Lead

2 weeks ago

Chennai, Tamil Nadu, India Buckman Full time

Position Summary

Buckman is seeking an experienced Data Science leader to lead the development of a Data Science program at our Chennai facility. You will work closely with Buckman stakeholders to derive deep industry knowledge across paper, water, leather, and performance chemical industries. You will help develop a data strategy for the company including collection of the right data, creation of the data science project portfolio, partnering with external providers, and augmenting capabilities with additional internal hires. A large part of the job is communicating and developing relationship with key stakeholders and subject matter experts to tee up proofs of concept projects to demonstrate how data science can be used to solve old problems in unique and novel ways. You will not have a large internal team to rely on, at least initially, so individual expertise, breadth of data science knowledge, and ability to partner with external companies will be essential for success. In addition to the pure data science problems, you will be working closely with a multi-disciplinary team consisting of sensor scientists, software engineers, network engineers, mechanical/electrical engineers, and chemical engineers in the development, and deployment of IoT solutions. If you like working for an entrepreneurial company with a Sustainability mission and digital ambitions at the core of its strategy, Buckman is the place for you.

Competencies Needed for Success Bachelor's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science 8+ years of relevant working experience in an analytical role involving data extraction, analysis, and visualization Expertise in one or more programming languages R, Python, MATLAB, JMP, Minitab, Java, C++, Scala Key libraries such as Sklearn, XgBoost, GLMNet, Dplyr, ggplot, Rshiny Experience and knowledge of data mining algorithms including supervised and unsupervised machine learning techniques areas such as Gradient Boosting, Decision Trees, Multivariate Regressions, Logistic regressions, Neural Network, Random Forest, Support Vector Machine, Naive Bayes, Time Series, Optimization Microsoft IoT/data science toolkit: Azure Machine Learning, Datalake, Datalake analytics, Workbench, IoT Hub, Stream Analytics, Cosmos DB, Time Series Insights, Power BI Data querying languages (. SQL, Hadoop/Hive) and Preferred Qualifications A demonstrated record of success with a verifiable portfolio of problems tackled

Preferred Qualifications

Master's or PhD degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science 3+ years of experience managing data science teams. Experience in the specialty chemicals sector or similar industry Background in engineering, especially Chemical Engineering Experience starting up a data science program Experience working with global stakeholders Experience working in a start-up environment, preferably in an IoT company Knowledge in quantitative modeling tools and statistical analysis

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