We are looking for a pragmatic, business-oriented Algo Team Lead to join our growing R&D team!

In this role, you won’t just build models, you will build the mathematical engine that drives Voyantis. Your mandate is dual: Innovate fast (prove value, solve cold starts) and Handover smooth (ensure successful integration into the core R&D product). You are the diplomat between the wild west of the CTO office and the structured world of Engineering.

About Us

Voyantis was founded in 2020 on the premise that market fundamentals are shifting companies worldwide from growth-at-all-costs strategies to efficient and responsible growth practices, with a focus on improving Unit Economics. With a bold mission to leverage AI to reimagine the whole Growth process, to streamline this transition and ensure its sustainability, Voyantis eliminates the guesswork from customer value creation, empowering leaders with actionable strategies and tactics to acquire, nurture and retain the high-value customers their businesses really need, with the actions and the timing that would be most impactful to achieve their goals.

Leading companies like Miro, Rappi and Moneylion rely on Voyantis to effectively apply these predictions. They use Voyantis to drive high-value customer acquisition on platforms like Google and Meta, optimize incentives through Salesforce and Braze, and perfectly time upsells, resulting in a 20%-40% ROI uplift.

Voyantis is well-backed by top VCs such as Target Global and SquarePeg. The company has tripled in size annually over the past two years and now boasts a team of 70 with offices in California, New York and Tel Aviv.

• Lead the Algo Roadmap - You will drive initiatives that directly impact our ability to grow, scale and move faster. Topics in our roadmap include Lifecycle Modeling, Uncertainty Estimation, Deep Learning for Tabular Data and more.
• Bridge the Gap - Design the process for graduating a successful prototype from the CTO Office to the core R&D team. You ensure innovation doesn't become technical debt. Decide when an algorithm is good enough to be put in front of internal users. You optimize for speed-to-value over academic perfection.
• Solve Real World ML Challenges - Implement strategies to handle prediction drifts and sudden spikes. Solve for "Insufficient data for customer" scenarios. Leverage LLMs and Agents not just for the product, but to multiply your team's output.

• A business-driven ML thinker who knows how to turn high-level goals into measurable, value-driven models.
• A fast mover with strong engineering instincts — able to innovate quickly while collaborating smoothly with Engineering.
• Clear judgment on build vs. buy decisions, choosing the right level of complexity for real-world impact.
• Full-stack ML awareness, understanding that production, stability, and delivery are as critical as the model itself.
• Strong hands-on experience with Python and modern ML stacks (Pandas, CatBoost, XGBoost, PyTorch, advanced ML techniques).
• Curiosity and experience around GenAI and AI agents; cloud and modern data stack experience (Snowflake, DBT, AWS/GCP) is a strong plus.