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- Tasks: Join us as a Senior Data Scientist to analyse data and drive insights for our social media app.
- Company: Luupli is an innovative social media platform supporting diverse creators from marginalised communities.
- Benefits: Work remotely, gain equity in the startup, and transition to a paid role post-launch.
- Why this job: Be part of a mission-driven team shaping the future of social media for underrepresented voices.
- Qualifications: Bachelor's or master's in a relevant field with experience in AWS analytics and data science.
- Other info: This role is currently unpaid but offers significant equity and growth potential.
The predicted salary is between 36000 - 60000 £ per year.
Luupli is a social media app 'in-development', which will provide opportunities for diverse creators coming from marginalized communities. Luupli will highlight the work of diverse creators and provide them access to all the opportunities in the social media space.
Work Arrangement
The commitment required from you is a few hours a week, working remotely, until our global launch next year. While this role is currently unpaid, you will be given a vested equity in our startup, together with a range of vested benefits. Once the app launches in the spring of 2024, this role will transition into a paid full-time role.
As a Data Scientist at Luupli, you will play a pivotal role in leveraging AWS analytics services to analyse and extract valuable insights from our data sources. You will collaborate with cross-functional teams, including data engineers, product managers, and business stakeholders, to develop data-driven solutions and deliver actionable recommendations. Your expertise in AWS analytics tools and techniques will be crucial in shaping our data strategy and driving business growth.
Responsibilities:
- Collaborate with cross-functional teams to understand business objectives, identify data requirements, and define analytics goals.
- Develop and implement data analysis strategies using AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight.
- Design and build robust data pipelines and ETL processes to extract, transform, and load data from diverse sources into AWS for analysis.
- Apply advanced statistical and machine learning techniques to perform predictive and prescriptive analyses, clustering, segmentation, and pattern recognition.
- Identify key metrics, develop meaningful KPIs, and build dashboards and visualisations using Amazon QuickSight to enable data-driven decision-making.
- Conduct exploratory data analysis to uncover trends, patterns, and insights that inform product enhancements, user behaviour, and engagement strategies.
- Collaborate with data engineers to optimise data architecture, data quality, and data governance frameworks in AWS.
Requirements:
- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, or a related field.
- Proven experience as a Data Scientist, preferably in a cloud-based environment using AWS analytics services.
- Strong proficiency in AWS analytics services, such as Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight.
- Solid understanding of data modelling, ETL processes, and data warehousing concepts.
- Proficiency in statistical analysis, data mining, and machine learning techniques.
- Proficiency in programming languages such as Python, R, or Scala for data analysis and modelling.
- Experience with SQL and NoSQL databases, data visualisation tools, and statistical packages.
- Strong analytical, problem-solving, and critical thinking skills.
- Experience with social media analytics and understanding of user behaviour.
- Familiarity with big data technologies, such as Apache Hadoop, Apache Spark, or Apache Kafka.
- Knowledge of AWS machine learning services, such as Amazon SageMaker and Amazon Comprehend.
- Experience with data governance and security best practices in AWS.
- Excellent communication and collaboration skills to effectively work in a cross-functional team environment.
- Strong attention to detail and ability to deliver high-quality work within deadlines.
Compensation
This is an equity-only position, offering a unique opportunity to gain a stake in a rapidly growing company and contribute directly to its success.
Senior Data Scientist, Machine Learning employer: Luupli
Contact Detail:
Luupli Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist, Machine Learning
✨Tip Number 1
Familiarise yourself with AWS analytics services, especially Amazon Redshift and Amazon QuickSight. Being able to demonstrate your hands-on experience with these tools during discussions will set you apart from other candidates.
✨Tip Number 2
Showcase your understanding of social media analytics and user behaviour. Prepare examples of how data-driven insights can enhance user engagement on social platforms, as this aligns closely with Luupli's mission.
✨Tip Number 3
Network with professionals in the data science and social media sectors. Engaging with communities or attending relevant meetups can provide valuable insights and connections that may help you land the role.
✨Tip Number 4
Prepare to discuss your experience with machine learning techniques and how they can be applied to real-world problems. Be ready to share specific projects or case studies that highlight your analytical skills and problem-solving abilities.
We think you need these skills to ace Senior Data Scientist, Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with AWS analytics services. Emphasise any projects or roles where you've used tools like Amazon Redshift or Amazon QuickSight.
Craft a Compelling Cover Letter: In your cover letter, express your passion for supporting diverse creators and how your skills can contribute to Luupli's mission. Mention specific experiences that align with the responsibilities outlined in the job description.
Showcase Technical Skills: Clearly list your proficiency in programming languages such as Python or R, and your experience with SQL and NoSQL databases. Provide examples of how you've applied machine learning techniques in previous roles.
Highlight Collaboration Experience: Since the role involves working with cross-functional teams, include examples of past collaborations. Describe how you’ve worked with data engineers or product managers to achieve common goals.
How to prepare for a job interview at Luupli
✨Showcase Your AWS Expertise
Make sure to highlight your experience with AWS analytics services during the interview. Be prepared to discuss specific projects where you've used tools like Amazon Redshift or Amazon QuickSight, and how they contributed to data-driven decision-making.
✨Demonstrate Collaboration Skills
Since this role involves working with cross-functional teams, share examples of how you've successfully collaborated with data engineers, product managers, or business stakeholders in the past. Emphasise your communication skills and ability to understand diverse perspectives.
✨Prepare for Technical Questions
Expect technical questions related to data modelling, ETL processes, and machine learning techniques. Brush up on your knowledge of statistical analysis and be ready to explain your approach to solving complex data problems using Python or R.
✨Understand the Company’s Mission
Familiarise yourself with Luupli's mission to support diverse creators from marginalised communities. Be prepared to discuss how your skills can contribute to this goal and why you are passionate about working in a social media environment that prioritises inclusivity.
