Summary
A data scientist will work independently and have a good understanding of a range of topics, including data science techniques, delivery methods and stages (such as minimal viable products), tools and technologies.
At this role level, you will:
develop complex solutions using a range of data science techniques, whilst understanding any ethical considerations
understand the role and benefits of data science within the organisation
support capability building within the organisation
collaborate with others to develop data science solutions and outputs supporting the organisation
prepare and manipulate data, and perform complex analytics
present and communicate effectively
Work Activity Components
Title | Details |
---|---|
Model evaluation and advice (Level Three)(DATS) | Evaluates the outcomes and performance of data science models. Identifies and implements opportunities to train and improve models and the data they use. Publishes and reports on model outputs to meet customer needs and conforming to agreed standards. |
Technical Skills
Title | Details | Depth |
---|---|---|
Big Data | The discipline associated with data sets so large and/or complex that traditional data processing applications are inadequate. The data files may include structured, unstructured and/or semi-structured data, such as unstructured text, audio, video, etc. Challenges include analysis, capture, curation, search, sharing, storage, transfer, manipulation, analysis, visualization and information privacy. | Familiar with |
Business Environment | The business environment relating to own sphere of work (own organisation and/or closely associated organisations, such as customers, suppliers, partners and competitors), in particular those aspects of the business that the specialism is to support (i.e. localised organisational awareness from a technical perspective). | Familiar with |
Programming Languages | A set of codes and syntax (supported by software tools) that enables the unambiguous translation of specified functionality into source code for the creation of computer programs. | Familiar with |
Training
Title | Details |
---|---|
Data Management | Data management concepts, methods, tools and techniques relating to the planning, development, implementation, administration and curation of data. |
Numerical Analysis Methods and Techniques | Numerical analysis methods and techniques and how they can enable the specification of options and associated action plans for the implementation of IT-enabled business processes. Numerical analysis may cover costing, logistics optimisation, econometric modelling as well as decision rules. |
Professional Development Activity (PDA)
Title | Details | PDA Group |
---|---|---|
Communications | Undertaking learning and practice in oral and written communications, including report writing and presentation. | Developing Professional Skills |
Deputising | Standing in for supervisor or manager on a temporary basis during periods of absence. | Broadening Activities |
Gaining Knowledge of Employing Organisation | Gaining basic knowledge of the employing organisation, its business, structure, culture, policies, products/services, operations and terminology. | Increasing Knowledge |
Gaining Knowledge of the Technical Environment | Gaining knowledge of IT activities in the employing organisation. | Increasing Knowledge |
Involvement in Professional Body Activities | Attending meetings, seminars and workshops organised by professional body and reading published material, such as journals and web content. | Participation in Professional Activities |
Job Shadowing and Special Assignments | Undertaking temporary periods or secondments in other roles, particularly those that offer a new perspective on own function or exposure to other environments and cultures. | Broadening Activities |
Research Assignments | Exploring a topic which is not part of own normal responsibilities and presenting findings to colleagues and/or management | Increasing Knowledge |
Qualification Components
Title | Awarding Bodies |
---|---|
FEDIP Practitioner | The Federation for Informatics Professionals |
Additional Frameworks
National Competency Framework for Data Professionals in Health and Care
Behaviours
Title | Details |
---|---|
Delivering outcomes (B1.1) (Level Two) | You initiate work with others in your team in order to bring about a generally agreed outcome. |
Communicating within a hierarchy (B1.2) (Level Two) | You are able to appeal to those in authority in order to facilitate influence. |
Generating consensus (B1.3) (Level Two) | You understand how to steer the direction of activity by influencing the consensus of opinion. |
Logical arguments (B1.4) (Level Two) | You understand how to structure a reasoned argument to influence the decisions of others. |
Negotiation (B1.5) (Level Two) | You are able to negotiate simple exchanges in order to achieve a specific result. |
Generating support (B1.6) (Level Two) | You understand how interpersonal skills such as kindness and compassion can increase people's desire to support you. |
Influence (B1.7) (Level Two) | You are generally able to identify when you are being influenced and assess the situation on its own merits. |
Equality (B2.1) (Level Two) | You consistently look to collaborate with colleagues who are representative of the protected characteristics in the Equality Act 2010 to work on any group and do not tolerate any implication that any group should be omitted from inclusion. |
Challenging discrimination (B2.2) (Level Two) | You articulate, when prompted, the fact that discrimination of any kind will not be tolerated by your organisation and report what you know to your line manager. |
NHS Constitution (B2.3) (Level Two) | You know the importance of following, and are familiar with, the behaviours and values listed in the NHS Constitution. |
Supporting others (B2.4) (Level Two) | You are kind to yourself, supportive of those around you and let someone know if things become difficult. |
Open environment (B2.5) (Level Two) | You have read your organisation's local and the NHS National Equality, Diversity and Inclusion policies and take time to actively listen to the lived experiences of underrepresented and marginalised groups, asking questions and escalating the concerns of your colleagues to your line manager. |
Written communication (B3.1) (Level Two) | You are able to convey complex written ideas and insights in a clear and concise manner. |
Discussing complex ideas (B3.2) (Level Two) | You are able to discuss complex ideas in a clear and concise manner. |
Delivering complex ideas (B3.3) (Level Two) | You are able to appear confident when conveying complex ideas and insights. |
Understanding new ideas (B3.4) (Level Two) | You are able to understand new and complex ideas when brought up in conversation. |
Reading audiences (B3.5) (Level Two) | You consistently check to ensure other parties have understood the message from your communication. |
Problem sharing (B4.1) (Level Two) | You regularly work on problems with colleagues in your team. |
Seeking opinions (B4.2) (Level Two) | You take time to elicit the input of others to a problem. |
Sharing best practice (B4.3) (Level Two) | You look to make successes part of your routine offering. |
Embedding best practice (B4.4) (Level Two) | You scan the successes of the team in order to improve your work. |
Patient impact (B5.1) (Level Two) | You understand the impact of your actions on patients. |
Understanding the customer (B5.2) (Level Two) | You spend time with the customer to understand what will add value to their requirement. |
Customer service (B5.3) (Level Two) | You use your knowledge and experience to offer alternative suggestions that would benefit the customer. |
Customer solutions (B5.4) (Level Two) | You regularly try new techniques to provide greater efficiencies for the customer or outcomes for the patient. |
Data Skills
Title | Details |
---|---|
Analytics techniques (DSC1.1) (Level Two) | You apply a range of techniques to transform data into valid and purposeful information. Undertakes analysis and data science activities to deliver analytical outputs in accordance with customer needs and as tasked within the project team. |
Analytics standards and policies (DSC1.2) (Level Two) | Ensures work conforms to agreed standards. |
Technique application (DSC1.3) (Level Two) | Seeks advice on the application of techniques when appropriate. |
Generating value (DSC1.14) (Level Two) | Analyses and reports findings and remedies simple issues using algorithms implemented in standard software frameworks and tools. |
Data science outputs (DSC1.4) (Level Two) | Applies existing data science techniques to new problems and datasets using specialised programming techniques. |
Evaluating data science techniques (DSC1.5) (Level Two) | Evaluates and reports on the outcomes and performance of data science systems and models. |
Professional development (Data Science) (DSC2.2) (Level Two) | Actively identifies and takes opportunities to further own professional development. |
Professional networking (Data Science) (DSC2.3) (Level Two) | Takes advantage of opportunities to share own knowledge / expertise. |
Quality Assurance (Data Science) (Level Two) | Provides quality assurance of data science work using appropriate guidance and frameworks and takes account of ethical considerations. |
Control (DSC2.9) (Level Two) | Contributes to documentation to assure that appropriate quality control activities and ethics considerations have taken place. |
Reporting (DSC3.1) (Level Two) | Reports own analytical work in sufficient detail, presenting results in both written and oral form. |
Key messages (DSC3.2) (Level Two) | Identifies key messages from the work and translates these into terminology suitable for either technical or non-technical audiences. |
Explanation and recommendation (DSC3.3) (Level Two) | Explains the evidence provided by own analysis and comments on the context and connections of interest to the customer of the analysis. |
Tailored presentation (DSC3.4) (Level Two) | Clearly explains the implications of the analysis for the project / policies under examination or the impact on operational processes and/or research being undertaken. |
Data visualisation (Data Science) (DSC3.5) (Level Two) | Presents data and data science outputs through various visual techniques and provides clear narratives using appropriate language that meets customer needs. |
Improving outputs (DSC3.6) (Level Two) | Supports data preparation from existing sources. |
Tool selection (DSC3.7) (Level Two) | Selects appropriate visualisation techniques and tools from the options available. |
User needs (DSC3.8) (Level Two) | Engages with users directly and/or works with user interface designers to prototype and refine specified visualisations. |
Opportunities (Level Two) | Looks for ways to improve ways of working within current area of responsibility, suggesting novel uses of existing data and technology. |
Experimentation (Level Two) | Experiments with innovations, manages and learns from failures and shares lessons learned within the team. |
Alternative solutions (Level Two) | Contributes ideas as part of team discussion when engaged in specific projects. |
Innovation strategy (Level Two) | Looks for ways to automate and improve efficiency of repeatable analytical workflows. |
Data transformation (Data Science) (Level Two) | Applies robust and ethical techniques in the transformation of data from one format or medium to another in line with organisational policies and procedures. |
Data exploration (Level Two) | Uses data exploration techniques to help evaluate the characteristics of a dataset and its suitability for subsequent analysis. |
Data warehousing (Data Science) (Level Two) | Understands and assists in the development and modification of source data e.g. data pipelines, datasets, data stores and metadata in accordance with established processes. |
Existing data sources (Level Two) | Shares knowledge of data sources with colleagues. |
Analytical potential (Level Two) | Uses defined data modelling and design techniques under guidance. |
Data integrity (Level Two) | Makes effective use of available data sources using appropriate methods to extract data for analysis in an ethical manner. |
Data linking (Level Two) | Creates new datasets through the manipulation of multiple data sources, including linking or matching data using techniques already established in the work area. |
Data sources (Level Two) | Recognises where external data sources can be integrated with own datasets. |
Data quality (Data Science) (Level Two) | Carries out routine data quality checks and remediation such as handling missing data or outliers and performing data cleansing. |
Data structures (Level Two) | Documents and communicates the details of data structures to others. |
Accessibility (Level Two) | Performs administrative tasks to ensure accessibility, retrievability, security and protection of data. |
Programming (Data Science) (Level Two) | Plans, designs, creates, amends, refactors, verifies, tests and documents simple to moderately complex programs/scripts. |
Development approaches (Level Two) | Develops expertise in available tools and infrastructure and shares this with others. |
Engineering standards (Level Two) | Applies agreed standards, version control and tools, to achieve a well-engineered result. |
Development reviews (Level Two) | Collaborates in reviews of work with others and is able to code with others using an agreed platform and versioning methodology such as git. |
Development standards (Data Science) (Level Two) | Seeks to maximise reusability and reproducibility of developed code and practices, such as Coding in the Open, and shares developments with colleagues. |
Advanced Statistics (Level One) | You understand when advanced inferential statistical techniques are needed and the different methods available. You are able to build basic regression models and analyse results from three or more groups. |
Machine Learning (Level One) | You understand the principles behind machine learning and their link to predictive analysis. You can identify the data needed for successful machine learning to take place and understand the iterative nature of machine learning. |
Hypothesis Testing (Level One) | You can identify a business question and convert it into an appropriate hypothesis. You understand the difference between analytical hypotheses and null hypotheses. You understand one-sided and two-sided hypotheses. |
Behavioural Science (Level One) | You can identify problems effectively and are able to gather research from multiple areas and contexts. |
Social Research (Level One) | You are able to think logically and have an interest in the issues relating to society, groups and individuals. |
Economics (Level One) | You can utilise quantitative research skills including knowledge of statistical techniques used in applied economics. |
Operational Research (Level One) | You have a good understanding of the strengths and limitations of OR techniques. |
Project Skills
Title | Details |
---|---|
Business cases (WP1.1) (Level Two) | You advise on the effort required and perceived risks and benefits during the development of business cases. |
Scope (Level Two) | You ensure the team's work conforms to project scope, adjusting as necessary following any authorised changes, allocating work efficiently whilst maintaining quality standards within the allocated timescales. |
Reviews (Level Two) | You report progress effectively using the project management framework in use demonstrating accountability for the team's output. |
Advice and monitoring (Level Two) | You advise on data and digital project plans to ensure they thoroughly encompass all the activities and resources required to ensure a successful outcome and that the planned benefits can be realised. |
Complexity (Level Two) | You understand and can articulate when the complexity of a proposed project requires further professional management or support. |
Scheduling (Level Two) | You schedule project work appropriately for yourself and the team, ensuring business needs are met both within the project and in business as usual. |
Refinement (Level Two) | You refine the plan within your work area to take account of any authorised changes communicating actions, progress and results with project managers. |
Resource identification (Level Two) | You identify the resources required to fulfil the project plan's requirements. |
Skill acquisition and management (Level Two) | You plan for the recruitment of staff with additional required skill sets, liaising with HR and/or other providers to source skilled staff to fulfil project roles. |
Additional tools and resources (Level Two) | You plan for the acquisition, deployment and support of additional tools and resources such as hardware, software and data sources for the course of the project. |
Resource allocation (Level Two) | You plan the allocation of existing resources to project work whilst effectively maintaining business as usual wherever feasible. |
Project management (Level Two) | You identify and co-ordinate team project-related activities to conform to cost, time and quality limitations, reporting and, where approriate, managing any risks and issues locally. |
Pilots and testing (Level Two) | You advise on or lead pilot and testing programs and report on progress, findings and lessons learned. |
Implementation (Level Two) | You engage with project co-ordinators and change agents to facilitate the implementation of a project and nurture its sustainability. |
Communications (Level Two) | You communicate effectively with others, adapting your style and approach as and when required. |
Business change (Level Two) | You understand the business case for change and how your team can facilitate that change. |
Assurance (Level Two) | You contribute to ideas generation and the evaluation of appropriate solutions which deliver the intended business benefits. |
Evaluation (Level Two) | You are an advocate for the project and the benefits to be realised. |
The Professional Body Responsible for this job family is AphA. This job role profile was created in collaboration with BCS, using Role Model Plus.