Position : Data Scientist
Buckman is seeking an experienced Data Scientist to lead the development of a Data Science program. 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.
- Bachelor’s degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science
- 5+ years of relevant working experience in an analytical role involving data extraction, analysis, and visualization and expertise in the following areas:
- 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, CosmosDB, Time Series Insights, PowerBI
- Data querying languages (e.g. SQL, Hadoop/Hive) and Preferred Qualifications
- A demonstrated record of success with a verifiable portfolio of problems tackled
- Master’s or PhD degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science
- 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
- A strong business focus, ownership and inner self-drive to data science solutions to real-world customers with tangible impact.
- Ability to collaborate effectively with multi-disciplinary and passionate team members.
- Ability to communicate with a diverse set of stakeholders
- Strong planning and organization skills, with the ability to manage multiple complex projects
- A life-long learner who constantly updates skills
Engineering Information Technology
Biotechnology Chemicals Paper & Forest Products