At a Glance
- Tasks: Design and implement advanced machine learning systems for retail data analysis.
- Company: Join a stealth-mode VC-backed startup revolutionising shopping experiences with behavioural AI.
- Benefits: Enjoy competitive pay, equity options, and a dynamic, collaborative work environment.
- Why this job: Make a real impact on retail while working with cutting-edge technologies and industry experts.
- Qualifications: 3-5+ years in data science, MSc in a related field, and expert Python skills required.
- Other info: Ideal for energetic individuals eager to thrive in a fast-paced, innovative setting.
The predicted salary is between 48000 - 84000 Β£ per year.
Direct message the job poster from algo1
We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up β no legacy, no patchwork systems β just a clean slate and a clear vision. Our mission is to build products that customers love by harnessing cutting-edge AI to transform their shopping experience.
About the Job
We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You\’ll be working across our entire data science stack, from advanced recommender systems to comprehensive performance analytics.
Key Responsibilities:
- Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling.
- Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems.
- Bring your models to production and optimise for inference in edge computing environments.
Essential Qualifications:
- 3-5+ years implementing advanced data science solutions in a commercial setting.
- MSc in Computer Science, Machine Learning, or a related field.
- Experience building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt).
- Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting.
- Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code.
Desired Skills (Bonus Points):
- Strong practical understanding of retail analytics including consumer segmentations, personalisation systems, campaign effectiveness and media measurement.
- Experience with recommender systems and/or behavioural AI.
What We Offer:
- Opportunity to build technology that will transform millions of shopping experiences
- Real ownership and impact in shaping our product and company direction
- A dynamic and collaborative work environment
- A chance to work with cutting-edge technologies and solve challenging problems
- Competitive compensation
- Equity in a rapidly growing company
If you\’re an energetic data scientist who thrives in a fast-paced environment and wants to make a real impact on the future of retail, we encourage you to apply.
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Job function
Engineering and Research
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Industries
Software Development
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Senior Data Scientist employer: algo1
Contact Detail:
algo1 Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Senior Data Scientist
β¨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and data science, especially in areas like recommendation systems and reinforcement learning. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the role.
β¨Tip Number 2
Network with professionals in the behavioural AI and retail analytics space. Engaging with industry experts can provide valuable insights and potentially lead to referrals, which can significantly increase your chances of landing an interview.
β¨Tip Number 3
Showcase your practical experience by discussing specific projects where you've implemented advanced data science solutions. Be prepared to explain the challenges you faced and how you overcame them, as this will highlight your problem-solving skills.
β¨Tip Number 4
Stay updated on the tools and technologies mentioned in the job description, such as Apache Spark and Kafka. Being able to speak confidently about these tools during discussions will demonstrate your readiness to contribute effectively from day one.
We think you need these skills to ace Senior Data Scientist
Some tips for your application π«‘
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, data science, and any specific tools mentioned in the job description, such as Apache Spark or Python. Use keywords from the job posting to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for behavioural AI and retail analytics. Discuss how your previous work aligns with the company's mission and how you can contribute to their goals. Be specific about your achievements in bringing data science solutions to production.
Showcase Your Projects: If you have worked on relevant projects, especially those involving recommender systems or generative AI, include them in your application. Provide links to your GitHub or portfolio to demonstrate your coding skills and project outcomes.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms and data pipelines. Brush up on your knowledge of deep learning, predictive analysis, and edge computing environments, as these are crucial for the role.
How to prepare for a job interview at algo1
β¨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and data pipelines. Highlight specific projects where you've implemented advanced data science solutions, especially in a commercial setting.
β¨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Be ready to explain how you approach complex data analysis and optimisation problems, particularly in edge computing environments.
β¨Understand the Companyβs Mission
Familiarise yourself with the startup's focus on behavioural AI and retail. Be ready to discuss how your skills can contribute to their mission of transforming shopping experiences through cutting-edge technology.
β¨Prepare for Cultural Fit Questions
As a VC-backed startup, cultural fit is crucial. Be ready to share examples of how you've thrived in fast-paced environments and collaborated with cross-functional teams to drive impactful results.