Data Scientist Job Description
Job Summary-Data Scientist Job Description
A Data Scientist has strong technical knowledge in one data science area
and a good general knowledge of the whole field. Responsible for modelling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, and visualisation techniques.
In addition to advanced analytic skills, Lead Data Scientists are also proficient at integrating and preparing large, varied datasets, architecting specialised databases, and communicating results. Will have a combination of business focus, strong analytical and problem solving skills and programming knowledge and are able to quickly cycle through hypothesis. They are able to use their excellent written and communications skills to influence a broad set of stakeholders.
Key Responsibilities- Data Scientist Job Description
• Accountable for agreed / allocated data science initiatives. That includes coordination and work planning of data scientist and technical teams, as well as keeping the stakeholders engaged and informed
• A lead data scientist will line manage a team of data scientists and is responsible for their delivery, coaching and development
• Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our customers interact with our content and services and recognise new service opportunities from data and insight
• Solve problems and identify trends and opportunities coming from data and automation
• Applies advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems
• Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices
• Develops innovative and effective approaches to solve analytics and systematic problems and communicates results and methodologies
• Presents and depicts the rationale of their findings in easy to understand terms for the business.
• Educates the organisation both from technology and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results. Helps the organisation understand the concept and the math behind the process to drive organisational buy-in
• Provides business metrics for the overall project to show improvements (contribution to the improvement should be monitored initially and over multiple iterations). Implements a model management methodology to ensure that we know when our models are no longer performing as expected
• Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, rationality , significance, and fairness
• Provides on-going tracking and monitoring of performance of decision systems and statistical models
Knowledge, skills, training and experience-Data Scientist Job Description
• Masters in mathematics, statistics or computer science or related field; OR equivalent
• Substantial relevant quantitative, qualitative research and analytics experience.
• Solid knowledge of statistical techniques.
• The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
• Strong programming skills (such as Hadoop MapReduce or other big data frameworks, Java), statistical modeling (like Python or R).
• Strong experience using machine learning algorithms.
• Proficiency in the use of statistical packages.
• Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
• Very strong communication and interpersonal skills.
• Experience guiding and coaching teams.
• In-depth industry/business knowledge.
• Contributing to the development of area of specialism or industry domain
• A mix of public sector and commercial experience
• Participation in published documents within your area of specialism
• Successful academic background in your specialist discipline
• Provides a management role in the development and implementation of data science capability and standards; promoting best practice within the area of business
• Assessing for value-for-money options for business as usual and emerging technologies
• Assessing the appropriate mix of build/buy options within the area of business taking into account strategic direction, business flexibility and emerging disruptive tech