• Collaborate with business stakeholders to understand data needs and objectives. • Extract, clean, and preprocess data from various sources for analysis. • Develop predictive models, statistical analyses, and algorithms to solve complex business problems. • Build tools to automate data collection. • Create and maintain interactive dashboards and reports using Power BI. • Perform ad-hoc data analysis to support decision-making. • Conduct data exploration and visualization to identify trends and patterns. • Stay up-to-date with the latest industry trends and best practices in data analysis and Power BI.

Lightricks is an AI-first company creating next-generation content creation technology for businesses, enterprises, and studios with a mission to bridge the gap between imagination and creation. At our core is LTX-2, an open-source generative video model, built to deliver expressive, high-fidelity video at unmatched speed. It powers both our own products and a growing ecosystem of partners through API integration. The company is also known globally for pioneering consumer creativity through products like Facetune, one of the world’s most recognized creative brands, which helped introduce AI-powered visual expression to hundreds of millions of users worldwide. We combine deep research, user-first design, and end-to-end execution from concept to final render, to bring the future of expression to all. What you will be doingOur Data Science team is high-impact. Our models directly impact budget planning, marketing spend allocation, and product prioritization. We're building an agentic AI ecosystem that shapes how we research, ship, and monitor across the company. We're hiring a Senior Data Scientist with strong NLP and ML skills. You'll build classification, scoring, and prediction models across both B2B and B2C domains - lead prediction, account health monitoring, revenue and marketing forecasting, and extracting signals from unstructured user data. You'll also contribute to the team's AI ecosystem, including evaluating and calibrating AI agent outputs, and work on ML projects across our revenue and marketing portfolio. Our stack: Python, BigQuery, GCP, our own production pipeline framework, Prefect, and Grafana. We're looking for someone with strong modeling instincts who cares about business impact - not just technical depth, but making sure the work lands and changes how decisions are made. - Build classification, scoring, and prediction models across B2B and B2C domains - lead scoring, account health monitoring, user segmentation, among owning ML projects across the team's portfolio - Design text-based features from noisy, real-world user data - prompts, project metadata, usage patterns — where off-the-shelf embeddings aren't necessarily enough and domain-specific signal extraction matters - Evaluate, calibrate, and improve AI agent outputs - measuring accuracy, and identifying failure modes in AI-generated results - Lead projects end-to-end: from identifying a business problem with stakeholders, through DS project planning and research, to production deployment and integration - Apply DS solutions to solve business problems across Finance, Marketing, Product, and other internal teams Your skills and experience - M.Sc. or Ph.D. in Statistics, Computer Science, Mathematics, or a related quantitative field - 5+ years of hands-on data science experience - Proven experience deploying NLP or text-based models into production environments - Strong programming skills in Python and SQL (BigQuery or equivalent) - Experience with ML frameworks; familiarity with time-series methods is a plus - End-to-end project experience: from business problem definition through research, modeling, production, and stakeholder delivery - Proven experience working with both unstructured and structured data - Daily use of AI tools in your workflow - you already work with LLMs, coding assistants, or AI-powered tooling as a natural part of how you get things done - Strong communication skills - ability to present complex technical findings clearly to non-technical audiences, and collaborate effectively across teams Good to haves - Experience with anomaly detection or unsupervised methods - Experience evaluating, calibrating, or benchmarking LLM and AI agent outputs - Fine-tuning or RAG production experience Why Join Us:We’re here to push the boundaries of what’s possible with AI and video - not for the buzz, but for the craft, the challenge, and the chance to make something genuinely new. We believe in an environment where people are encouraged to think, create and explore. Real impact happens when people are empowered to experiment, evolve, and elevate together. At Lightricks, every breakthrough starts with great people and a collaborative mindset. If you're looking for a place that combines deep tech, creative energy, and zero buzzword culture, you might be in the right place. We got you covered!We empower employees with cutting-edge tools and learning opportunities to grow and succeed through workshops, access and training on platforms, subscriptions, and clear guidelines for responsible AI use. We offer Car-to-go subscriptions and run daily door-to-door shuttles from several locations in central Israel, plus free parking and train-station pickups. We’re proud to have 2 chef-led restaurants on site by the legendary Machneyuda Group (yes, that Machneyuda!), plus a bakery nestled in the heart of our office, filled daily with the scent of fresh pastries.

Role Description We are seeking a highly motivated and hands-on Data Scientist / Senior Data Engineer to help build and scale KPI’s Closed-Loop Design Program — an initiative focused on accelerating pre-sales engineering, improving automation design accuracy, and leveraging AI-driven insights across the customer solution lifecycle. This role sits at the intersection of: - Data Engineering - Applied AI & Analytics - Supply Chain Automation - Solution Design You will work closely with solution architects, engineering teams, and business stakeholders to transform RFPs, customer requirements, and historical project data into intelligent, repeatable outputs that drive faster and more accurate proposal development. This is an exciting opportunity for someone who enjoys building systems from the ground up, solving complex operational problems, and influencing how advanced automation solutions are designed and delivered. What You’ll Deliver: High-Impact Use Cases - RFP & Specification Intelligence: Extract requirements, generate compliance matrices, and identify clarifying questions automatically. - Cost & ROI Scenario Modeling: Support data-driven decision-making through option comparisons and sensitivity analysis. - Proposal “Fact Pack” Automation: Create scalable executive summaries and SOW-ready proposal content from governed datasets. - Design & Operational Analytics: Analyze throughput, staffing models, slotting strategies, and replenishment impacts. - Benchmark-Driven Solution Guidance: Leverage historical project data and comparable implementations to guide future designs. What You’ll Do - Build and maintain curated datasets using Databricks (Delta tables, jobs, SQL Warehouses) and SQL-based governed reporting tables. - Ingest and manage full pursuit lifecycle artifacts including RFPs, specifications, drawings, and addenda with proper metadata and version control. - Develop applied analytics solutions including: - Forecasting - Scenario modeling - Optimization (LP/MILP or practical heuristics) - Similarity modeling and benchmarking - Publish reliable datasets and insights for Tableau Cloud consumption with consistent business definitions. - Establish a closed-loop learning cycle by comparing design assumptions against operational outcomes to continuously improve benchmarks and estimate accuracy. - Partner cross-functionally with engineering, analytics, and solution design teams to improve automation decision-making at scale. What Success Looks Like - Accelerate proposal development with intelligent, governed “first draft” solution packs. - Improve confidence and accuracy in complex automation pursuits. - Build scalable benchmarking capabilities that improve operational estimates over time. - Create data products that directly influence automation strategy and customer outcomes. Qualifications - 4+ years of experience in: - Data Science - Analytics Engineering - Applied Machine Learning - Strong SQL skills including: - Data modeling - Query optimization - Governance-ready dataset development - Hands-on experience with Databricks (Delta Lake, notebooks, jobs, SQL Warehouses) or similar enterprise data platforms. - Strong Python experience preferred for: - Data preparation - Modeling - Workflow automation - Ability to communicate assumptions, risks, and analytical outcomes clearly to technical and non-technical stakeholders. Preferred Qualifications - Experience in warehouse automation or intralogistics environments: - AMRs - AutoStore - Shuttle systems - Sortation - WES/WCS platforms - Experience with: - Forecasting - Optimization - Simulation / Digital Twin technologies - Decision-support analytics - Familiarity with document parsing and extraction workflows for RFP/specification processing. - Tableau experience including: - Curated dataset publishing - Dashboard performance optimization Benefits - Medical Insurance - Dental Insurance - Vision Insurance - Health Care Concierge Service - 401(k) Retirement Plan (Pre-tax & Roth) - Company paid Basic Life Insurance, Short-Term Disability & Long-Term Disability - Voluntary Life & AD&D Insurance - Voluntary Accident, Critical Illness & Hospital Indemnity Insurance - Pet Insurance - Milk Stork Program - Wellness Program with gift card redemption and wellness challenges - Paid Time Off (Vacation, Sick & 10 Holidays) - Training & Development

• Build, validate, and deploy statistical and machine learning models (e.g. anomaly detection, fraud detection, clustering, NLP, generative AI). • Experiment with advanced techniques (e.g. graph neural networks, LLMs, deep learning) to push the boundaries of what data can deliver. • Collaborate with engineering, product, and business teams to translate strategic questions into data-driven solutions. • Contribute to architectural discussions on scalable, production-ready ML systems. • Share your knowledge with a team of passionate engineers and help foster a culture of agile, data-driven decision-making.