Data Scientist Team Lead
Lead and mentor a team of data scientists at Arpeely, whose programmatic ad-acquisition engine makes billions of sub-second ad-buying predictions daily and is now building Ace AI, an AI-native browser. The role combines hands-on ML, Python, and big-data analysis with data strategy and cross-functional leadership.
- Compensation
- Not disclosed
- Location
- Tel Aviv-Jaffa, Tel Aviv District
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Two years of experience in leading a team
- 4+ years of practical analytics experience in big data businesses (preferably B2C)
- Hands-on, passionate about algorithms, data, and business
- Excellent analytical skills with experience querying large, complex data sets
- Strong understanding of statistical significance
- Hands-on experience with machine learning algorithms, Python, and data visualization tools (Tableau, Looker, etc.)
- BSc degree (or higher) in Mathematics, Statistics, Engineering, Computer Science, or another quantitative field
- Self-learner, multi-tasker, able to work independently
- Self-sufficient, proactive problem-solver
- Excellent communication skills, written and verbal
- Fun to work with and a team player
Nice to have
- Familiarity with the ad-tech industry
- Experience implementing real-time machine learning and data mining algorithms in large-scale environments
Full description
About Us
Arpeely is bootstrapped and has been profitable since day one. We built one of the most efficient programmatic acquisition engines on the planet: processing billions of ad decisions a day, generating terabytes of live behavioral data, and turning it into margins most SaaS companies would kill for.
At the core of that engine is a team of data scientists and ML engineers running tens of billions of sub-second predictions a day, deciding in milliseconds which impression is worth buying and what it’s worth.
Now we’re taking everything we’ve learned about how people move through the web and putting it into our most innovative consumer product yet: Ace AI, an AI-native browser already reaching millions of people, built to simplify and improve everyday online life with the help of AI.
This is a rare opportunity: a category that hasn’t meaningfully changed in over a decade, and a profitable company with the data and the acquisition engine to win it on its own terms.
Come build it with us.
What You’ll Do
- Mentor a team of extremely talented and success-hungry data scientists.
- Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
- Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
- Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
- Identify and propose data science and algorithmic solutions for various product initiatives.
- Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
- Partner with other departments (e.g. Management, R&D, Product) to support decision making.
Requirements
- Two years of experience in leading a team.
- 4+ years of practical analytics experience in big data businesses (preferably at a B2C company).
- A hands-on, passionate person who likes to get to the bottom of things in terms of algorithms, data, and business.
- Excellent analytical skills with experience in querying large, complex data sets.
- Strong understanding of statistical significance.
- Hands-on experience with machine learning algorithms; Python and data visualization tools such as Tableau, Looker, etc.
- BSc degree (or higher) in Mathematics, Statistics, Engineering, Computer Science, or any other quantitative field.
- Self-learner, multi-tasker, able to work independently.