At a Glance
- Tasks: Design and develop AI solutions while collaborating with a dynamic team.
- Company: Join a leading firm in AI and machine learning within the financial sector.
- Benefits: Competitive pay, hybrid work model, and opportunities for professional growth.
- Other info: Exciting contract role with potential for ongoing opportunities.
- Why this job: Make an impact by solving complex problems with cutting-edge technology.
- Qualifications: Experience in Python, SQL, and machine learning model development required.
The predicted salary is between 60000 - 80000 £ per year.
We're looking for a Data Scientist to join a major AI and machine learning programme focused on delivering production-grade models and data science solutions across a range of business-critical initiatives. The role is hands-on, covering model development, deployment, validation, feature engineering, and data analysis within an established delivery team.
Key Responsibilities:
- Design and develop AI and machine learning solutions
- Build, validate, and deploy production-ready models
- Perform exploratory data analysis and feature engineering
- Develop classification, ranking, and anomaly detection models
- Support machine learning deployment within containerised environments
- Troubleshoot and debug code across the development life cycle
- Work closely with technical and business stakeholders to solve complex problems
- Produce technical documentation and support model governance activities
Key Skills:
- Experienced within Financial Services
- Strong Python experience (pandas, NumPy, scikit-learn)
- Strong SQL skills
- Experience developing and validating machine learning models
- Experience with classification, ranking, and unsupervised learning techniques
- Experience deploying machine learning solutions into production
- Familiarity with Git and collaborative development practices
- Experience working with time-series data and trend analysis
- Strong exploratory data analysis skills
Additional:
- Experience with SHAP, LIME, model monitoring, or drift detection
- Knowledge of rank aggregation techniques such as Robust Rank Fusion (RRF)
- Experience within regulatory, risk, financial crime, or compliance environments
- Experience with record linkage, entity resolution, or network analytics
- Exposure to graph databases and technologies such as Neo4j, Neptune, Cypher, or Gremlin
Key Details:
- Rate: Dependant on Experience
- Location: London (Hybrid)
- Duration: 6 Month Contract (rolling)
- Start: Immediate
Data Marketing Scientist in London employer: Orbis Group
Join a forward-thinking company at the forefront of AI and machine learning in London, where innovation meets collaboration. As a Data Marketing Scientist, you'll thrive in a dynamic work culture that values creativity and problem-solving, with ample opportunities for professional growth and development. Enjoy the unique advantage of working in a hybrid environment, allowing for flexibility while contributing to impactful projects that shape the future of financial services.
StudySmarter Expert Advice🤫
We think this is how you could land Data Marketing Scientist in London
✨Showcase Your Skills with a Public Portfolio
As a freelancer in data science, having a killer portfolio is essential. Showcase your projects on platforms like GitHub or create a personal website that details your work and techniques. This gives potential clients a clear picture of what you can do and helps you stand out from the competition.
✨Get Involved in Data Science Communities
Tap into online forums like Kaggle or Stack Overflow. Not only can you showcase your expertise, but you can also connect with other data scientists and potential clients. Plus, participating in competitions and discussions can elevate your profile in the field.
✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
✨Pitch Your Services Directly to Companies
Don't just wait for freelancing platforms to bring clients to you—be proactive! Research companies that could benefit from data science services and craft tailored pitches. Mention specific pain points you can address for them. Let’s get that freelance hustle going!
We think you need these skills to ace Data Marketing Scientist in London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Data Marketing Scientist at Orbis Group, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at Orbis Group.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at Orbis Group
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
