Lead Data Scientist job description

Job brief

The Head of Data Science plays a leadership position in the data science department and is responsible for overseeing activities of the junior data science team ensuring proper execution of duties and alignment with the business’s overall vision. The Head of Data Science is responsible for the creation of new data sciences capabilities for the business by envisioning and executing strategies that will influence improvement of the business’s performance by enabling informed decision making.

Responsibilities

• training and professional development of Analysis and Insights staff
• standardisation of methods and algorithms used, including artificialintelligence and machine learning
• provision of data science resources, including code libraries and documentation
• quality assurance of outputs
• ad hoc project work
• Lead and manage a team of data scientists that is innovative, collaborative, and customer focused.
• Responsible for data science professional development and training in the use of modern data sciencetools.
• Standardisation of methods and algorithms used across the business unit.
• Develop and maintain standard software libraries and associated documentation, includingimplementation of artificial intelligence and machine learning algorithms.
• Provision of resources and training to enable quality assurance of processes and outputs.
• Support the business unit transition from SAS, to alternative analytical programming languages.

Requirements

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. {{depending on specific project requirements}}. Excellence in at least one of these is highly desirable
• Great communication skills
• Experience with data visualization tools, such as D3.js, GGplot, etc.
• Proficiency in using query languages such as SQL, Hive, Pig {{actual list depends on what you are currently using in your company}}
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase {{depending on project needs}}
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills {{if you expect that the person in this role will integrate the solution within the base application, list any programming languages and core frameworks currently being used}}
• Data-oriented personality