At a Glance
- Tasks: Develop data models to drive business growth and influence sales strategies.
- Company: Global recruitment specialist with a focus on innovation and collaboration.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional development.
- Other info: Fast-paced environment with potential for career advancement.
- Why this job: Join a dynamic team and make a real impact on business decisions.
- Qualifications: 5+ years of SQL experience and strong problem-solving skills required.
The predicted salary is between 36000 - 60000 £ per year.
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Location: Reading (Hybrid – 3 days per week onsite)
Duration: 6 months contract initially
The Opportunity: The Data Science team is seeking a dedicated Data Science Engineer. This role provides an outstanding opportunity to work with exceptionally skilled professionals and influence our sales strategy directly. You will be instrumental in driving business growth by successfully implementing data-driven models that identify and size potential opportunities. You will work with senior stakeholders and team members to explore various data sources, engineer compelling features, then build, test, and evaluate models to prove their efficacy. Your ability to communicate complex model features to business owners will be essential for encouraging confidence and enabling sellers to drive impactful customer conversations. This is a fast-paced environment that requires the ability to make tactical decisions quickly to balance methodologies with business priorities.
What You Will Do:
- Develop and own rSAM models to size headroom opportunities in the book of business for specific offerings and customer segments
- Carry out in-depth business analysis to uncover the drivers behind performance gaps and make recommendations for change
- Engage with senior stakeholders to understand key growth areas and ensure solutions align with business priorities
- Assess and improve the performance of sales campaigns with performance insights and recommendations for model enhancements
- Support the customer segmentation process using rSAM and other insights
- Provide different models like customer segmentation based on clustering, customer lifetime value based on survival analysis, and forecasting
- Deliver channel segmentation to determine customer engagement strategy and optimize lifetime value
- Collaborate with data engineering teams to productionize data pipelines and drive scalable solutions
- Automate model refreshes and account prioritization processes
- Build propensity models to drive sales campaigns using predictive modelling techniques.
What You Will Bring:
- 5+ years of SQL experience for querying, cleansing, integrating, and summarizing complex data is essential
- Experience with Databricks and Python is desirable
- Proven experience of building, testing, evaluating, and improving revenue-generating data science models
- Knowledge of propensity modeling techniques and other modeling techniques would be beneficial
- Proven experience translating complex analytics into understandable insights for senior collaborators is essential
- Strong problem-solving skills and experience in a fast-paced business environment with changing requirements.
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often shortlisted within 48 hours.
Data Science Engineer in Reading employer: eTeam
Join our dynamic team in Reading as a Data Science Engineer, where you'll collaborate with top-tier professionals in a hybrid work environment that promotes flexibility and innovation. We prioritise employee growth through continuous learning opportunities and a supportive culture that values your contributions to impactful business strategies. With a focus on data-driven decision-making, you'll play a crucial role in shaping our sales initiatives while enjoying the benefits of working in a vibrant and fast-paced setting.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Engineer in Reading
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common data science questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and skills.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your best work, especially any models or analyses you've done. This will give potential employers a tangible sense of your capabilities and creativity.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we often have exclusive roles listed that you won’t find anywhere else.
We think you need these skills to ace Data Science Engineer in Reading
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Science Engineer role. Highlight your SQL, Python, and data modelling expertise to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this position. Share specific examples of how you've driven business growth through data-driven models in the past.
Showcase Your Communication Skills:Since you'll be working with senior stakeholders, it's crucial to demonstrate your ability to translate complex data insights into clear, actionable recommendations. Let us see this in your application!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any updates from our team!
How to prepare for a job interview at eTeam
✨Know Your Data Science Models
Make sure you brush up on the data science models mentioned in the job description, like rSAM and propensity models. Be ready to discuss how you've built, tested, and improved these models in your previous roles.
✨Communicate Complex Ideas Simply
Since you'll need to explain complex model features to senior stakeholders, practice simplifying your explanations. Use analogies or real-world examples to make your points clearer and more relatable.
✨Showcase Your SQL Skills
With 5+ years of SQL experience being essential, prepare to demonstrate your querying and data manipulation skills. You might be asked to solve a problem on the spot, so review common SQL queries and data cleansing techniques.
✨Understand Business Priorities
Familiarise yourself with the company's sales strategy and how data science can influence it. Be prepared to discuss how your insights can align with business goals and drive growth, showing that you understand the bigger picture.
