Data Scientist

Description

Data Scientist

[Freelance, Full-time, Remote GMT+0/GMT+4]

SNEAK PEEK

⇨ Location: Remote, GMT+0/GMT+4

⇨ Salary: between $5K - $6.5K per month

⇨ Interview process: HR interview ⇨ technical discussion ⇨ take-home challenge ⇨ final interview 

⇨ Contact: For questions please reach out to: hr@rounds.com 

WHO ARE WE? 

At Rounds, we believe in harnessing the power of cutting-edge technology to drive business success. Our transformative, machine-learning technology identifies and optimizes mobile assets, while our team of experts, with their unparalleled human capital and business acumen, provides the strategic direction and support to turn mobile assets into profitable businesses. Together, we are revolutionizing the mobile industry. You can find out more info about us and our values here: www.rounds.com. 

THE ROLE

We are looking for an ambitious Data Scientist who is eager to embark on an exciting journey as the first official Data Scientist in our team. The role requires the optimization of a huge amount of previously untapped data resources, providing you the opportunity to explore the latest and most innovative technologies, tools, and methodologies in collaboration with our team. Your contributions in this role are instrumental, with potential to significantly impact areas such as acquisitions, development, finance etc. We highly value your hands-on approach, not only in conducting cutting-edge research but also in translating those insights into practical, production-ready solutions.

Hiring manager: Yossi Wasserman, VP of R&D Engineering

         (https://www.linkedin.com/in/yossi-wasserman)

RESPONSIBILITIES:

• Develop and implement statistical models, machine learning algorithms, and other advanced analytical techniques to extract insights from structured and unstructured data
• Perform exploratory data analysis to uncover patterns, trends, and actionable insights to guide product development and business strategy
• Build prediction systems and optimize models leveraging techniques like regression, classification, and clustering
• Design and run A/B tests, user behavior analyses, and other experiments to inform product decisions
• Communicate results and insights clearly to both technical and non-technical stakeholders
• Stay up-to-date on the latest data science and machine learning advancements and apply them as appropriate

NICE TO HAVE:

• Experience with Vertex AI or other ML ops platforms

Requirements

WHAT ARE WE LOOKING FOR?

• Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative field (MSc or PhD would be nice to have)
• 3+ years of experience building and deploying machine learning models in a production environment
• Proficiency with Python data science libraries (NumPy, Pandas, Scikit-Learn) and experience with big data platforms (Spark, Hadoop would be nice to have)
• Strong statistical modeling and machine learning skills (regression, classification, clustering, neural networks)
• Ability to communicate complex analyses and results in a clear, structured manner to non-technical audiences
• Passion for translating data into product and business impact

HOW DO WE WORK?

We are a distributed team of more than 60 people, all working remotely and communicating partially synchronously (we usually overlap with our team for 4 hours daily and are free to work on some of the tasks whenever it suits us best). We value open communication, proactivity and work/life balance and we measure our freelancers on performance, rather than on the time spent on the job.

WHAT’S IN IT FOR YOU? 

• Fully remote work model 
• Flexible full-time working hours 
• Competitive pay in the range of $5K - $6.5K based on skills and experience 
• The opportunity to grow together with the company & take ownership from day 1

INTERESTED?

Our recruitment process consists of the following steps: 

• HR interview: 60 min.
• Technical discussion: 60 min. 
• Paid take-home challenge: 1 day
• Final interview with the hiring manager and CTO: 30 min.

Get in touch at hr@rounds.com. We’d love to hear from you!