Data Scientist (IL)

About Us

Latent AI is a leading AI solutions implementation partner with an established and diverse international client base, dedicated to solving complex challenges through cutting-edge technology. Our strength lies in our global workforce – comprising small, agile, and expert teams distributed around the world who deliver bespoke AI and machine learning solutions. We foster a culture of collaboration, innovation, and deep technical excellence that connects our talent and clients across borders.

Company Website

https://www.reachlatent.com/

The Role

We are seeking an experienced and proactive Senior Data Scientist to join our team. This role focuses on transforming complex datasets into actionable insights and building robust machine learning solutions, with a strong emphasis on rigorous experimentation, statistical rigor, and timely delivery.

The ideal candidate is comfortable exploring messy real-world datasets, designing experiments, developing and optimizing predictive models, and communicating findings clearly to both technical and non-technical audiences. This role suits someone who is proactive, intellectually curious, and can work independently.

What You'll Do

• Modeling & Analysis: Lead end-to-end development of machine learning and statistical models, from problem framing and feature engineering through to evaluation, iteration, and handoff to production.
• Data Exploration & Pipeline Collaboration: Dive deep into complex datasets to surface insights and work closely with engineers to define and validate the data pipelines that feed model development.
• Benchmarking & Evaluation: Design and maintain robust evaluation frameworks for models, providing data-driven insights that inform modeling decisions, vendor selection, and architectural trade-offs.
• Structured Experimentation: Hypothesize, design, implement, and measure experiments to identify optimal modeling approaches and generate actionable optimization steps.
• Technical Point of Contact: Serve as the data science lead on projects, engaging directly with customers' R&D and analytics teams, translating their business questions into well-defined modeling problems and driving tangible impact through your expertise.
• Project Delivery Oriented: Hold a deep sense of accountability for your analysis and models, their quality, and timely delivery. Own the design, planning, and execution of the data science workstreams.
  
  

• Collaborative Contributor: You identify gaps, define clear assumptions, and raise critical flags early to ensure team alignment and project progress.
• Execution-Focused Builder: You own tasks from inception to completion, translating ambiguous business questions into rigorous analyses and models that consistently meet production standards.
• Proactive Communicator: You engage stakeholders and team members directly; rather than waiting for information, you seek it out to keep momentum moving forward.
• Analytical Problem Solver: You contribute meaningfully to technical discussions and offer actionable recommendations, maintaining a clear path forward even when navigating ambiguity.
• Continuous Learner: You stay at the forefront of the field by actively reviewing academic papers and emerging research to integrate the latest advances in ML and data science into your work.
  
  

• Master's in Statistics, Data Science, Computer Science, Mathematics, or similar experience
• Strong foundation in statistical modeling, machine learning, and model evaluation techniques
• Proficiency in designing and running structured experiments, including A/B testing and causal inference methods
• Hands-on experience with supervised and unsupervised learning across a range of problem types (classification, regression, clustering, time-series, etc.)
• Experience working with LLMs and GenAI techniques as tools within the data science workflow
• Excellent written and verbal communication skills in English, capable of translating complex analytical findings into clear, actionable narratives for technical and non-technical audiences
• Strong programming skills in Python, including the data science stack (pandas, scikit-learn, etc.)
• Comfort working with and querying large datasets using SQL or similar tools
• Strong analytical and problem-solving skills with a healthy skepticism toward results
• Ability to work in a dynamic, fast-paced environment
• Proven ability to work independently, proactively own outcomes, and contribute effectively as part of a small, close-knit team