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For Companies At a Glance
- Tasks: Dive into data analysis, experimentation, and product design with a focus on user experience.
- Company: Join a leading tech company known for innovation and impact in the digital space.
- Benefits: Enjoy a competitive daily rate, remote work flexibility, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that shapes user experiences and drives impactful product decisions.
- Qualifications: Must have a master's degree and 10-15 years of experience in data science or related fields.
- Other info: Immediate start available for a 10-month contract; perfect for seasoned data enthusiasts.
The predicted salary is between 85000 - 110000 £ per year.
Job details
Posted 02 February 2025
Salary £425 – £500 per day, Benefits: Negotiable
Location London
Job type Contract
Discipline Data
Reference BH-113236
Contact Name Nathan Peters
Job description
Data Scientist – HIRING ASAP
Start date: ASAP
Duration: 10 Months
Location: Remote
Rate: £425 – £500 per day PAYE.
Interview Process: 2 stages.
Skills:
- 10-15 years’ experience
- Experimentations for user facing products.
- Narrative excellence
- Data querying language: SQL
- Statistical or mathematical software including one of the following: R, SAS, or MATLAB
- Applied statistics or experimentation, such as A/B testing, in an industry setting.
- Ability to write queries.
- Experience working on an app or a website, for Big Technology businesses like Netflix, Amazon, Spotify, etc.
- Requires a master’s degree in computer science, Engineering, Information Systems, Analytics, Mathematics, Economics, Physics, Applied Sciences, or a related field.
- Performing quantitative analysis including data mining on highly complex data sets.
- Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics.
- Enjoys getting their hands dirty to understand data and system disconnects and can drive insightful root-cause-analysis.
- Passionate about building solid and scalable measurement solutions.
Responsibilities:
- Work with the engineering teams, product managers, design teams, etc.
- Cover Appeals for account enforcements, i.e. when we take an action on a user or advertiser’s account.
- Support both strategically and operationally in our highest priority area.
- Improve the mechanisms that exist to appeal (e.g. Consider account disables, feature limits and lightweight enforcements)
- Identify how we meet the needs and expectations of our users and what opportunities there are to improve.
- Balance reducing harm on the platform with protecting voice and revenue, alongside regulation and cost guardrails.
- Align the business on your improvement ideas and support their implementation.
- Work closely with data partners to establish or improve our measurement capabilities.
- Collect, organize, interpret, and summarize statistical data to contribute to product design and development.
- Apply expertise in quantitative analysis, data mining, and the presentation of data.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Inform, influence, support, and execute product decisions and launches.
- May be assigned projects in various areas including product operations, exploratory analysis, product influence, and data infrastructure.
- Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
- Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
- Perform data analyses on tactical and strategic work to drive team direction.
- Develop strategic narrative based on analytical insights and priorities.
- Think about key questions and metrics to define success for any product/feature.
- May apply knowledge of quantitative analysis techniques, data querying languages, scripting languages, and statistical or mathematical software.
- Communicate the results of analyses to product or leadership teams to influence strategy.
- Machine learning techniques
- ETL (Extract, Transform, Load) processes.
- Relational databases
- Large-scale data processing infrastructures using distributed systems.
Bonus Skills:
- Python/R
#J-18808-Ljbffr
Data Scientist V employer: Soda
Contact Detail:
Soda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist V
✨Tip Number 1
Make sure to showcase your experience with user-facing products during the interview. Highlight specific projects where you applied statistical techniques or A/B testing, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Familiarize yourself with the latest trends in data science, especially in relation to big tech companies like Netflix and Amazon. Being able to discuss current methodologies or tools they use can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your approach to root-cause analysis. Be ready to provide examples of how you've identified and resolved data disconnects in previous roles, as this aligns closely with the responsibilities of the position.
✨Tip Number 4
Since the role involves collaboration with various teams, practice articulating how you would communicate complex data insights to non-technical stakeholders. This skill is crucial for influencing product decisions and driving strategy.
We think you need these skills to ace Data Scientist V
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 10-15 years of experience in data science, particularly focusing on experimentation for user-facing products. Include specific examples of your work with SQL, R, SAS, or MATLAB.
Craft a Compelling Cover Letter: Write a cover letter that showcases your narrative excellence and passion for building scalable measurement solutions. Mention your experience with A/B testing and quantitative analysis techniques relevant to the role.
Highlight Relevant Projects: In your application, emphasize any projects you've worked on for big technology companies like Netflix, Amazon, or Spotify. Detail your contributions and the impact of your work on product design and development.
Prepare for the Interview: Since the interview process consists of two stages, prepare by reviewing common data science interview questions, especially those related to statistical analysis, data mining, and machine learning techniques. Be ready to discuss how you can influence product decisions with your analytical insights.
How to prepare for a job interview at Soda
✨Showcase Your Experience
With 10-15 years of experience required, be ready to discuss specific projects where you've applied your skills in data science. Highlight your work with user-facing products and any relevant experimentation techniques like A/B testing.
✨Demonstrate Narrative Excellence
Prepare to articulate complex data insights in a clear and compelling narrative. This role emphasizes the ability to communicate findings effectively, so practice summarizing your analyses and their implications for product design.
✨Familiarize Yourself with SQL and Statistical Software
Since proficiency in SQL and statistical software like R, SAS, or MATLAB is crucial, brush up on your querying skills and be ready to discuss how you've used these tools in past roles to drive insights from data.
✨Understand the Business Context
Research the company and its products thoroughly. Be prepared to discuss how your analytical skills can help improve user experiences and meet business objectives, especially in balancing user needs with regulatory requirements.
