Data Team Lead

Description At Leadspotting, we’re building platforms that transform complex data into clear, actionable intelligence. We’re looking for a Data Team Lead to take ownership of one of our core data groups — a team building advanced, scalable data pipelines and AI-powered models that deliver real-time insights for public and private sector decision-makers. As a hands-on leader, you’ll manage a multidisciplinary team of data engineers, scientists, and analysts. You’ll work closely with product, engineering, and domain experts to drive the development of intelligent, data-driven products — using modern tools like PySpark, SQL, LLMs, transformers, and knowledge graph modeling. If you're passionate about AI, data architecture, leadership, and turning messy, complex data into clarity and impact — this is your place. Key Responsibilities Lead a team of data scientists in developing GEN-AI driven NLP, CV, Big data analytics solutions. Architect Design, and optimize LLMs, Agentic AI, transformer models, RAG pipelines, and classical ML/NLP/CV pipelines. Work closely with Fullstack teams, and Product Managers and talented data engineers to integrate AI models into production systems. Balance between 70% product delivery and 30% research, collaborating with a dedicated research team. Engage with operational customers to understand their needs and translate them into AI-driven solutions they can trust. Requirements Required Qualifications Must-Haves 2+ years of hands-on experience in AI/ML, with a focus on designing, training, and deploying LLMs and NLP models. With focus on text and topic analysis. 3+ years of experience leading AI or data science teams, including mentoring, goal settings. Technical leadership. Proven track record in LLMs (GPT, LLaMA, Falcon, etc.), RAG pipelines, semantic search, Agentic or transformer-based architectures. Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow. Experience deploying production-grade AI models in both cloud and on-prem environments, ensuring scalability and performance. Ability to collaborate effectively with engineers, PMs, and operational customers to translate AI research into product features. Nice-to-Haves Eligibility for Security Clearance Level 2 (active clearance – advantage). Hands-on experience with knowledge graphs, topic modeling, or multimodal AI. Familiarity with MLOps stacks (MLflow, Kubeflow, SageMaker, Vertex AI) and monitoring/observability for ML models. Experience with Generative AI in production (fine-tuning, prompt engineering, safety/guardrails). Knowledge in Palantir Foundry- for managing and integrating complex datasets. Knowledge of data anonymization, encryption, and compliance frameworks (ISO, NIST, SOC 2). Background in defense, mission-critical, or applied AI at scale. Excellent leadership, problem-solving, and decision-making skills.