Senior Data Scientist

The Clients Data Science team delivers insights and value to clients from heterogeneous data sets with solutions that integrate into engineering and decision-making processes. Additionally, their team enables big data analytics for their clients through advisory services including use case prioritizations, tool selection and training, and capability definitions. Their success as a services firm relies on their experts' ability to be more than technologists and statisticians.

The Senior Data Scientist will be responsible for utilising advanced statistical and machine learning methods to answer business questions and deliver insightful solutions to complex problems. The ideal candidate has excellent interpersonal and communication skills and can interact with business and technology stakeholders where necessary.

Specific Responsibilities

The Senior Data Scientist will:

• Design hypothesis tests, oversee test execution, and evaluate the results
• Model, predict and classify data
• Utilise machine learning and large-scale data mining techniques to discover and identify actionable patterns in the data

Customer workshops:

• Help define and document business requirements and acceptance criteria
• Assist in or lead workshops and documenting relevant outcomes
• Identify opportunities and appropriate solutions (e.g. algorithms and libraries)
• Present to both technical and non-technical stakeholders, internally and in a Customer facing capacity

Agile cross-functional teamwork:

• Contribute to sprint planning, provide realistic estimates and plan deliverables
• Attend standups and retrospectives
• Research, design, evaluate, build, tune and document end to end data science solutions
• Understand and solve scalability and production issues

Documentation and coding standards:

• Adhere to coding standards and best practices
• Ensure all models are validated and all business logic is robustly tested

The following are a list of relevant skills expected from the successful candidate:

Must

• Have a minimum of five years professional experience
• Have clear written and spoken English
• Have experience presenting to business stakeholders
• Have experience formalising data science solutions based on a set of business requirements
• Have demonstrable experience of delivering a data science solution to production
• Have knowledge and experience of the products software lifecycle
• Have an excellent understanding of machine learning and statistics
• Have well-developed quantitative skills and analytical thinking
• Have experience in scaling data science methods and accounting for non-functional requirements
• Have demonstrable professional experience in Python or R
• Have demonstrable professional experience in Scala, Java or C
• Be proficient with version control tools and strategies, ideally Git and Gitflow
• Have hands-on work experience with:

Data analysis and visualisation tools and workbenches

Analysing structured, semi-structured and unstructured data

Data query languages, e.g. SQL, HiveQL or similar

• Have experience in working in cross-functional agile software engineering teams
• Have experience in reliably estimating, planning and meeting deadlines for deliverables
• Have experience mentoring Junior Data Scientists

Should

• Hands-on work experience/proficient with:

Spark

Scikit-learn and Pandas

• Have experience with integrating Data Science within products or enterprise solutions

Desirable

• Hands-on work experience/proficient with:

Distributed systems

Hadoop ecosystem

Cloud-based machine-learning APIs

• Have sufficient knowledge of NLP
• Have experience with TDD, BDD and Continuous Integration