Description:
The opportunity is a highly rewarding role for individuals who are excited about the opportunities that analytics create in all aspects of business and society, you might be a great fit for our Agility Ventures team if you have a passion for Data analytics.
Our Data Scientists work closely with the senior management team to deliver intellectual capital and solutions that enable our clients to derive maximum value from their data while resolving their most pressing business needs.
The Department
Agility's Center of Excellence is the innovation hub and digital accelerator of its global logistics business. We develop, identify, acquire, evaluate, pilot and deploy tomorrow’s tools and technologies – including IoT, AI, machine learning, data analytics and block chain. This successful CoE builds and broadens technological competency across Agility’s global network, creating a company that is more powerful, focused, efficient and competitive.
Come join us to build the next leader in the logistics space with the best of what technology has to offer today. Help us solve the toughest of challenges through technology.
Your Responsibilities
You will be charged with continuing to build the technology that powers our core business which includes:
- Collaborate with business stakeholders throughout the company to identify opportunities where data science techniques can deliver business value. Translate complex business problems into data science projects.
- Derive actionable insights from large, structured, semi-structured and unstructured data sets
- Clearly document and communicate the outcomes of the data science initiatives and make sure that the insights and findings can be clearly understood by business stakeholders and translated into actions
- Formulate, develop, and implement end-to-end data science solutions to solve business problems using machine learning and operations research techniques
- Coordinate with internal stakeholders to deploy data science models into production and monitor their performance
- Develop processes and tools to monitor and analyze models performance and data accuracy
- Work with external partners, service providers, and research institutions to deliver viable solutions
- Keep abreast of industry trends and emerging methodologies to continuously improve skillset
- Contribute to knowledge sharing and improve team productivity through training / documentation of best practices
Your Experience
- Minimum 3 years’ hands-on experience delivering data science solutions that work at scale for production usage
- Data mining techniques and advanced machine learning algorithms such as Random Forest, SVM, XGBoost, and deep learning, etc
- Mathematical programming and optimization solvers, such as Cplex, Gurobi, Xpress, etc. Deep learning frameworks (Tensorflow, Keras, etc.)
- Statistical languages and common data science toolkits / libraries, such as R, NumPy, Pandas, MatLab, etc.
- Extracting, transforming and working with large sets of data. Query and scripting languages such as SQL, Hive, Pig, ETL tools.
- Big data technologies (Spark and Hadoop ecosystem)
- Object oriented programming languages such as Python, Java, C++, Scala, etc.
- Relational databases and NoSQL databases, such as Cassandra, MongoDB, HBase, etc
- Experience with DataOps / DevOps frameworks (Git, CI / CD, Docker), an advantage
- Experience with data visualization tools, such as D3.js, GGplot, etc., an advantage
Your Proficiencies
- Strong analytical skills in mathematics, statistics, and computer science
- Creative problem solving attitude with a focus on timely delivery and ownership of results
- Attention to detail and ability to work in high pressure environment
- Excellent presentation and communication skills and the ability to communicate ideas effectively, at all levels throughout the organization.
- Natural curiosity to learn technologies, business models, and industry trends
Your Qualifications
- MSc (or PhD) in a quantitative field such as Computer Science, Operations Research, Applied Mathematics, Industrial / Systems Engineering, Applied Statistics, etc.
- Preferably with an undergrad in either Statistics, Mathematics, Operations Research, EE, CS, or related fields.