Senior Data Analyst

Made Tech wants to positively impact the country's future by using technology to improve society, for everyone. We want to empower the public sector to deliver and continuously improve digital services that are user-centric, data-driven and freed from legacy technology. A key component of this is developing modern data systems and platforms that drive informed decision-making for our clients. You will also work closely with clients to help shape their data strategy

As a Senior Data Analyst, you may play one or more roles according to our clients' needs. The role is very hands-on and you'll support as a senior contributor role for a project, focusing on

• **:

Data analysis and reporti
ng: Conducting in-depth data analysis, generating reports, and providing actionable insights for client project
- s.Data and BI visualisatio
n: Producing BI dashboards using industry-standard tools - Power BI, Tableau, Quicksight e
- tcClient interacti
on: Collaborating with clients to understand their needs, translating these into analytical solutions, and presenting findings in a clear, actionable manne
- r.Mentori**
ng junior analysts, leading data-focused projects, and setting best practices in data analys

is

You'll need to have a drive to deliver outcomes for users. You'll make sure that the wider context of a delivery is considered and maintain alignment between the operational and analytical aspects of the engineering soluti

**on.

Key responsibili**

**ties

Analysis and synt**

• hesisApplication of analytical techn
  iques: Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis. Ability to select and apply appropriate techniques based on the context and research
• data.Synthesis of research
  data: Experience in synthesising research data to present actionable insights and solutions. Ability to articulate the impact of their analysis on decision-making and problem-sol
• ving.Engagement with sceptical colleag
  ues: Effective communication and persuasion skills to engage and gain buy-in from sceptical colleagues. Ability to foster collaboration and address concerns to ensure adherence to best pract
• ices.Advisory and critique sk
  ills: Capability to advise on the choice and application of analytical techniques and critique colleagues' findings to ensure high standards in data anal

**ysis.

Data Mana**

• gementUnderstanding of data sources and s
  torage: Knowledge of various data sources, data organisation, and storage practices. Commitment to maintaining data integrity and accessib
• ility.Advocacy for data gove
  rnance: Experience in advocating for data governance standards and influencing team adherence to data quality prac
• tices.Continuous improve
  ment: Ability to communicate and implement continuous improvements in data management practices through documentation, training, and regular team engag
• ement.Toolset mana
  gement: Proficiency in defining and supporting common toolsets for data management, ensuring efficiency and seamless integr
• ation.Automation of data mana
  gement: Experience in automating data management activities to streamline processes and increase accuracy. (desi
• rable)Compliance with data governance po
  licies: Understanding and ensuring compliance with data governance policies, maintaining data security and ethical stan

**dards.

Data modelling, cleansing, and enr**

• ichmentData modelling ex
  pertise: Proficient in conceptual, logical, and physical data modelling. Ability to adhere to data modelling standards and best pra
• ctices.Data cleansing and standard
  isation: Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation tech
• niques.Use of data integration
  tools: Skilled in using ETL tools for data integration and storage. Ensures data interoperability with other da
• tasets.Collaboration with data profes
  sionals: Experience collaborating with other data professionals to improve modelling and integration standards and pa

**tterns.

Data Visua**

• lisationInterpretation of requi
  rements: Ability to interpret data visualisation requirements and create meaningful, visually appealing representations tailored to the a
• udience.Proficiency in visualisati
  on tools: Experience with tools such as Tableau, Power BI, and Python libraries like Matplotlib and Seaborn. Knowledge of selecting appropriate visualisatio
• n types.Application of visualisation st
  andards: Application of design principles to create clear, accurate, and accessible visualisations. Awareness of accessibility conside
• rations.Mentorship in visual
  isation: Experience in reviewing and advising junior members to improve the quality and efficiency of data visuali

**sations.

Data Quality Assurance, Validation, an**

• d LinkageData quality a
  ssurance: Experience in implementing processes for data quality assessment and improvement, including data profiling, cleansing, and standar
• disation.Data validation an
  d linkage: Ability to perform data validation checks and integrate data from various sources to ensure consistency and
• accuracy.Data cleansing and pre
  paration: Proficiency in defining data cleansing processes and preparing data for analysis by handling missing values, outliers, and du
• plicates.Communication of data li
  mitations: Skilled in articulating data constraints and limitations to stakeholders, providing context for informed decisio
• n-making.Peer review and qualit
  y control: Experience in conducting peer reviews to validate data outputs, ensuring high standards of accuracy and rel

**iability.

Statistical Methods and Dat**

• a AnalysisKnowledge of statistical met
  hodologies: Proficient in various statistical methods, such as hypothesis testing, regression analysis, clustering, and time series analysis. Ability to select appropriate techniques based on project req
• uirements.Data analysis and inter
  pretation: Experience in using statistical software or programming languages to perform data analysis and generate insights. Skilled in communicating findings to technical and non-technical sta
• keholders.Application of emerg
  ing theory: Willingness to explore and apply new statistical methodologies or practices to solve practical problems and adapt to emerging

**theories.

Skills, knowledge an**

**d expertise

C**

• ommunicationStakeholder c
  ommunication: Experience in effectively engaging with a diverse range of stakeholders, including technical and business individuals. Ability to manage expectations and facilitate productive
• discussions.Active and reactive c
  ommunication: Proficiency in handling both proactive communication (updates, insights) and reactive communication (responding to inquiries, addressing concerns) to maintain a collaborative
• atmosphere.Interpretation of stake
  holder needs: Ability to understand and translate stakeholder requirements into technical solutions. Experience in bridging the gap between technical and non-technical s
• takeholders.Presentation and sharing
  of insights: Skilled in presenting complex data in a clear, understandable manner tailored to diverse audiences, including senior

**management.

Logical and crea**

• tive thinkingProblem-sol
  ving approach: Ability to apply logical and creative thinking to resolve complex problems by breaking them down and generating innovati
• ve solutions.Decision-making and
  action-taking: Skilled in making informed decisions, prioritising tasks, and taking appropriate actions to resolve issues
• efficiently.Adaptability and learnin
  g orientation: Demonstrates adaptability in strategies and a commitment to continuous learning and
• improvement.Interpretation of stak
  eholder needs: Ability to understand and translate stakeholder requirements into technical solutions. Experience in bridging the gap between technical and non-technical

**stakeholders.

Presentation and shari**
ng of insights: Skilled in presenting complex data in a clear, understandable manner tailored to diverse audiences, including seni

or management.

At this point, we hope you're feeling excited about Made Tech and the job opportunity. Even if you don't feel that you meet every single requirement, we still encourage you to apply. Get in
touch with
our talent team if you'd like an informal chat about the role and your suitability before applying. We are hiring for this role directly, so will not respond to any CVs sent via external recrui
tment agencies.An increasing number of our customers are specifying a minimum of SC (security check) clearance in order to work on their projects. As a result, we're looking for all successful candidates for this role to have eligibility.Eligibility for SC requires 5 years' continuous UK residency and 5 year' employment history (or back to full-time education). Please note that if at any point during the interview process it is apparent that you may not be eligible for SC, we won't be able to progress your application and we will contact you to le

t you know w

hy.

Job benefitsWe are always listening to our growing teams and evolving the benefits available to our people. As we scale, as do our benefits and we are scaling quickly. We've recently introduced a flexible benefit platform which includes a Smart Tech scheme, Cycle to work scheme, and an individual benefits allowance which you can invest in a Health care cash plan or Pension plan. We're also big on connection and have an optional social and wellbeing calendar of events for all employees to join should

they choose to.Here are some of our most popular benefi

• ts listed below
  :

30 days Holiday - we offer 30 days of paid annual leave p
- lus bank holidaysFlexi
ble Working Hours - we are flexible with wh
- at hours you workFlexib
le Parental Leave - we offer flexible paren
- tal leave opti
onsRemote Working - we offer part time remote working
- for all our staf
fPaid counselling - we offer paid counselling as well as financial

and legal advice