You will be responsible for the data driven automations and synchronisations across departments to ensure that individual and departmental KPIs are met accordingly. Individual tasks vary depending on the size and structure of the organisation, but you'll need:
● 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 skill sets.
● Contribute to knowledge sharing and improve team productivity through training / documentation of best practices
● Minimum 3 years’ hands-on experience developing and applying data-driven solutions in a corporate or consulting setting, preferably in a consumer marketing context
● 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
● A Bacholors or Master’s degree in machine learning, mathematics, computer science, or related fields
● Experience with building predictive & forecasting models
● NLP Techniques
● Strong knowledge of data processing, data modelling, algorithms, and data architecture
● Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritise an approach for maximum impact
You'll need to show evidence of the following:
● 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