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- Tasks: Lead data analysis using AWS tools to drive insights and recommendations.
- Company: Join Luupli, a social media app empowering diverse creators from marginalised communities.
- Benefits: Equity-only compensation offers a stake in a growing company with impactful social goals.
- 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; experience with AWS analytics and data science required.
- Other info: This role is perfect for those passionate about data and social impact.
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.
As a Lead 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.
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.
Lead Data Scientist (Equity Only) - 1% employer: Luupli
Contact Detail:
Luupli Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist (Equity Only) - 1%
✨Tip Number 1
Familiarise yourself with AWS analytics services, especially Amazon Redshift and Amazon QuickSight. Being able to discuss specific projects or experiences where you've used these tools will show your expertise and make you stand out.
✨Tip Number 2
Network with professionals in the data science field, particularly those who have experience in social media analytics. Engaging with them can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with data pipelines and ETL processes. Be ready to share examples of how you've optimised data flow and improved data quality in previous roles.
✨Tip Number 4
Showcase your understanding of user behaviour and social media trends. Being able to connect your data analysis skills to real-world applications in social media will demonstrate your fit for Luupli's mission.
We think you need these skills to ace Lead Data Scientist (Equity Only) - 1%
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS analytics services and data science. Focus on relevant projects where you've used tools like Amazon Redshift, Amazon Athena, or machine learning techniques.
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 examples of how you've collaborated with cross-functional teams in the past.
Showcase Your Technical Skills: Include a section in your application that lists your technical proficiencies, especially in programming languages like Python or R, and your experience with data visualisation tools such as Amazon QuickSight.
Highlight Relevant Experience: When detailing your work history, emphasise any roles where you’ve worked in cloud-based environments or with social media analytics. This will demonstrate your understanding of user behaviour and data-driven decision-making.
How to prepare for a job interview at Luupli
✨Showcase Your AWS Expertise
Make sure to highlight your experience with AWS analytics services like Amazon Redshift and Amazon QuickSight. Be prepared to discuss specific projects where you've successfully implemented these tools to derive insights from data.
✨Demonstrate Collaboration Skills
Since the role involves working with cross-functional teams, share examples of how you've effectively collaborated with data engineers, product managers, or business stakeholders in previous roles. This will show that you can thrive in a team environment.
✨Prepare for Technical Questions
Expect technical questions related to data modelling, ETL processes, and machine learning techniques. Brush up on your knowledge of these areas and be ready to explain your thought process when solving data-related problems.
✨Understand the Company’s Mission
Familiarise yourself with Luupli's mission to support diverse creators. Be ready to discuss how your skills as a Data Scientist can contribute to this goal, particularly in understanding user behaviour and enhancing engagement strategies.