At a Glance
- Tasks: Analyse data to uncover insights and support social housing clients with actionable recommendations.
- Company: Join Mobysoft, a forward-thinking company dedicated to improving social housing through data solutions.
- Benefits: Enjoy a competitive salary, private healthcare, generous leave, and a supportive work environment.
- Other info: Collaborative team culture with opportunities for personal and professional growth.
- Why this job: Make a real difference in people's lives while developing your data analytics skills.
- Qualifications: 2-4 years in data analytics; strong skills in Python, SQL, and data visualisation tools.
The predicted salary is between 30000 - 40000 € per year.
Location: Manchester (This role can be based remotely but applicants must reside and have the right to work in the U.K)
Salary: Competitive plus excellent benefits
Skills Required
The successful candidate will have 2–4 years in a data analytics, data science, data insights, or analytics engineering role. Proven commercial experience is essential.
Who we are
Founded in 2003, Mobysoft provides data-based insight solutions to a wide range of social housing clients, through market-leading products, simultaneously helping keep tenants housed in homes they can enjoy and improving social housing landlords long term organisational health. Our vision is working towards a world in which intelligent technology significantly improves the quality of life for people who live in social housing and our mission is delivering accurate actionable data insights that help social housing providers ensure a consistent, equitable service.
What are we looking for?
We are an ambitious, hybrid working, customer‑centric Data & Analytics team, dedicated to developing a new generation of data products that unlock significant value for the social housing sector. We operate with a focused product lens, driven by curiosity and a commitment to technical excellence. As a Data Analyst you will work to bring together, explore and make sense of disparate data sources, which combine to create compelling stories for our clients such as developing trends and next best actions. In this role you will work across the full range of competencies (from analytical engineering and statistical analysis to visualisation and data storytelling). We’re not looking for unicorns, rather an enthusiastic, proactive data analytics professional with key foundational skills and experience, alongside a commitment to learn and develop new ones in role.
Key Responsibilities
- Data discovery. Evaluating new data sources and how they can enhance current/support new product propositions through appropriately designed experiments.
- Data trust. Providing analytics on the reliability of existing data including productionising ongoing monitoring with benchmarks.
- Sales support. Ensuring that our sales function is equipped with the metrics they need to support their success.
- Measuring success. Researching and developing appropriate measures of product effectiveness and return on investment (ROI) in collaboration with our sector experts.
- Strategic Analytics. Identifying our clients' and business' analytical needs, organising these into clear, actionable plans, and ensuring their effective execution.
- Feature generation. Working with our data science team to explore and develop new/improved data features.
- Insight Navigation. Liaising with our clients (directly or through events, conferences, webinars etc.), to help support their data driven journeys, finding the most compelling, clean and clear approach to effectively communicating their data insights story.
- Emerging technologies. Researching augmented analytics and related artificial intelligence (AI) approaches to enhance our output - helping to implement solutions where practical.
- Evolving standards. Working with the full Data & Analytics team to further enhance our systems of work.
Why should you consider this role?
Alongside the work opportunities as described your development will be supported, you will be sensibly remunerated, we will provide a compelling benefits package, and we are a great bunch of folks to work with - though we would say that!
Qualifications and skills – Required
- An honours degree with a substantial quantitative component / data analytics playing a key role.
- 2–4 years in a data analytics, data science, data insights, or analytics engineering role.
- Experience working with real‑world datasets, ideally in a commercial environment.
- Exposure to cross‑functional work for example, with data science, product and commercial teams.
- Data Wrangling & Transformation – strong experience shaping and preparing data across structured, semi‑structured, and unstructured formats; confident working with relational and non‑relational data sources; skilled in cleaning, joining, aggregating, and reshaping data for analysis and modelling.
- Data Pipelines & Modelling – hands‑on experience maintaining and creating ETL/ELT pipelines; solid understanding of data modelling principles (e.g., dimensional modelling, star schema, entity relationships); practical experience using DBT for SQL‑based transformations and modular modelling; familiarity with workflow orchestration and version‑controlled analytics engineering practices; exposure to cloud‑based data environments.
- Programming & Querying – proficient in Python and core analytics libraries (pandas, NumPy, SciPy, etc.); strong SQL skills; comfortable using Git for version control and collaborative development.
- Analytics, Statistics & Experimentation – strong grounding in statistical methods: hypothesis testing, regression (linear & logistic), correlation analysis, time series analysis.
- Visualisation & Reporting – skilled in Power BI and Excel; comfortable using notebooks (Jupyter) for exploratory analysis and experiment documentation; ability to translate complex findings into clear, compelling visual narratives.
Qualifications and skills – Desired
- Familiarity with Scala, HiveQL for data processing tasks.
- Understanding of Linux/Shell for data and environment operations.
- Experience working with Apache Spark and MapReduce for large‑scale data processing.
- Familiarity with NoSQL technologies such as Amazon DynamoDB.
- Machine Learning (ML) / predictive and prescriptive analytics experience.
- Hands‑on Tableau use.
What else are we looking for?
- Ability to work effectively both as an individual (e.g., during remote deep work) and within a team – supportive, collaborative.
- A keen interest in data analytics – bringing to the team new approaches, best practice developments and analytical methods from other walks of life.
- Clear written and verbal communication, including effective communication with non-technical audiences.
- Business acumen, i.e., understanding the business context with a proven ability to align and actively support business goals and OKRs.
- A good understanding of data governance and related best practice.
The Person
- Takes ownership and thrives on improving how things are done.
- Is proactive, self‑motivated, and solutions focused.
- Can influence and collaborate across teams.
- Is a critical thinker and a problem solver.
- Balances delivery detail with big‑picture thinking.
- Enjoys mentoring and helping others grow.
- Is curious to experiment, iterate, learn and develop.
- Is excited to help scale a values‑led SaaS company making a real difference.
Moby Ideals
- Customer‑focused: We drive outcomes that create value for the customer. We continually challenge ourselves on “what’s in it for the customer”. We drive win/win/win solutions.
- Collaborative: We operate as one, fostering open communication, diverse contribution, cooperation and trust. We inspire teams towards a common goal for success.
- Outcome‑orientated: We are driven by the end goal, rather than the process or steps to get there.
- Accountable: We own decisions, are transparent, set clear expectations and consistently deliver on commitments.
- Courageous: We actively contribute and constructively challenge with positive intent. We think big and move at pace.
- Innovative: We own and proactively search for solutions. We positively embrace problems and lead change.
Benefits
Competitive salary and rewards package including: private health care, 4 x salary life cover, 25 days annual leave, increasing to 28 after 3 years’ service, salary sacrifice pension scheme and much more.
Inclusion
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process - please contact us to request accommodation.
Data Analyst in Manchester employer: Mobysoft Ltd
Mobysoft is an exceptional employer that champions a hybrid working culture, fostering collaboration and innovation within the Data & Analytics team. With a commitment to employee development, competitive benefits including private healthcare and generous leave, and a mission that positively impacts social housing, Mobysoft offers a rewarding environment for data professionals eager to make a difference while growing their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or webinars, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Prepare for those interviews! Research Mobysoft and understand their mission and values. Think about how your skills in data analytics can help them achieve their goals, and be ready to share specific examples from your experience.
✨Tip Number 3
Show off your skills! Create a portfolio showcasing your data projects, visualisations, and any cool insights you've uncovered. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our awesome team at Mobysoft!
We think you need these skills to ace Data Analyst in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Analyst role. Highlight your relevant experience in data analytics, data science, and any specific tools or technologies mentioned in the job description. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about data analytics and how you can contribute to our mission at Mobysoft. Be sure to mention any specific projects or achievements that showcase your skills.
Showcase Your Technical Skills:Since this role requires strong technical skills, make sure to include any relevant programming languages, tools, and methodologies you've used. Whether it's Python, SQL, or data visualisation tools like Power BI, we want to know what you're capable of!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Mobysoft Ltd
✨Know Your Data
Before the interview, brush up on your data analytics skills. Be prepared to discuss specific projects you've worked on, especially those involving data wrangling and transformation. Highlight how you’ve used tools like SQL, Python, or Power BI to derive insights from data.
✨Understand the Company’s Mission
Familiarise yourself with Mobysoft's vision and mission. Understand how their data solutions impact social housing. This will help you align your answers with their goals and demonstrate your genuine interest in making a difference in the sector.
✨Prepare for Technical Questions
Expect technical questions related to data pipelines, statistical methods, and visualisation techniques. Practice explaining complex concepts in simple terms, as you may need to communicate findings to non-technical audiences. Use examples from your experience to illustrate your points.
✨Show Your Curiosity
Mobysoft values curiosity and a proactive approach. Be ready to discuss how you stay updated with emerging technologies and analytical methods. Share any recent learnings or experiments you've conducted that showcase your enthusiasm for data analytics.