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- Tasks: Analyse and validate data to ensure accuracy and reliability across our innovative platform.
- Company: Join Gifftid, a forward-thinking company transforming business data into actionable insights.
- Benefits: Remote/hybrid work options, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team dedicated to improving the real economy through trusted data.
- Why this job: Make a real impact by ensuring data integrity and supporting better decision-making for SMEs.
- Qualifications: 5+ years in data science, strong Python skills, and a knack for analytical thinking.
The predicted salary is between 60000 - 80000 £ per year.
Location: UK (Remote / Hybrid)
About Gifftid: Gifftid is building a platform that enables better decision-making by transforming fragmented business data into structured, meaningful intelligence. Many SMEs operate with strong fundamentals but lack the visibility required to access capital, partnerships, and growth opportunities. Gifftid brings together multiple data sources and applies structured analysis to support more informed, consistent, and transparent decision-making.
About the Role: We are looking for a Data Scientist to focus on analysing, validating, and refining data outputs across the platform. You will play a key role in ensuring that analytical models, signals, and outputs are accurate, reliable, and meaningful, supporting the overall integrity of the platform. This role combines data science, analytical thinking, and quality assurance.
Key Responsibilities:
- Analyse and interpret data from multiple sources;
- Develop and refine analytical models and scoring approaches;
- Validate outputs to ensure accuracy, consistency, and reliability;
- Identify anomalies, inconsistencies, and areas for improvement;
- Support the development of metrics and reporting frameworks;
- Collaborate with engineering teams to improve data pipelines and outputs.
Requirements:
- 5+ years experience in data science, analytics, or related fields;
- Strong Python skills (pandas, numpy);
- Solid grounding in statistics and data analysis;
- Experience working with structured and semi-structured data;
- Ability to translate complex data into clear insights.
Nice to Have:
- Experience with financial, operational, or business datasets;
- Familiarity with model validation or QA processes;
- Exposure to time-series or performance analytics.
What We’re Looking For:
- Strong analytical thinker with a critical mindset;
- Ability to question assumptions and validate outputs;
- High attention to detail and commitment to data integrity.
Why Join Gifftid:
You will help ensure that data and analytics are not just produced, but trusted and usable, contributing to a platform designed to improve how decisions are made in the real economy.
Apply: Contact Grace.Castillo@gifftid.com | Website:
Senior Data Scientist employer: Gifftid
Contact Detail:
Gifftid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects. Use platforms like GitHub to share your code and insights. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as communication is key in this field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your 5+ years in data science and any relevant projects that showcase your analytical thinking and Python skills.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to Gifftid's mission. Share specific examples of how you've validated data outputs or improved analytical models in the past.
Showcase Your Analytical Skills: In your application, don’t just list your skills—demonstrate them! Include examples of how you've identified anomalies or improved data integrity in previous roles. We love seeing real-world applications of your expertise.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Gifftid
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects and experiences with data analysis. Be ready to discuss specific datasets you've worked with, the challenges you faced, and how you validated your outputs. This will show your analytical thinking and attention to detail.
✨Brush Up on Python Skills
Since strong Python skills are a must for this role, make sure you're comfortable discussing libraries like pandas and numpy. Prepare to explain how you've used these tools in your previous work, especially in relation to data validation and model development.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Think of scenarios where you had to identify anomalies or inconsistencies in data. Be ready to walk through your thought process and the steps you took to ensure data integrity.
✨Showcase Your Collaborative Spirit
This role involves working closely with engineering teams, so be prepared to discuss your experience collaborating with others. Highlight any instances where you improved data pipelines or contributed to team projects, as this will demonstrate your ability to work well in a team environment.