Data Scientist - AI Engineer (PR-DS/AI-20250714)

We're a distributed SaaS company that leverages AI to provide media monitoring and analysis. Our tools help clients grasp what's being discussed globally and its significance. We transform raw data into actionable insights using large language models (LLMs), robust data pipelines, and tailored metrics.We're seeking a high-impact Data Scientist to reimagine and transform our operations and client product delivery. This strategic role merges advanced data science, LLMs, and product thinking to enhance simplicity, usability, quality, and operational efficiency across the company. We're looking for someone with 5+ years of experience, a profound understanding of LLMs (particularly the OpenAI ecosystem), and the ability to quickly integrate with our existing AI/ML team.You'll operate at the nexus of AI innovation, operational design, and client experience, applying technical rigor, business acumen, and creative energy to tackle complex challenges. Key Responsibilities LLM-led Innovation: Build and deploy LLM-powered tools and workflows that simplify analyst work, reduce errors, and accelerate delivery.Operational Transformation: Understand operational processes and create intelligent, scalable solutions that eliminate complexity and manual effort.Product Evolution: Partner with product and operations teams to infuse intelligence and automation into client-facing platforms.Client-Centric Design: Translate client pain points and product gaps into practical, data- driven AI solutions that enhance experience and outcomes.Rapid Experimentation: Prototype fast, test early, iterate often. Maintain speed without sacrificing accuracy or quality.Cross-Functional Collaboration: Work closely with engineering, product, client success, and operations teams to bring ideas to life. Tech Stack You’ll Work With: Languages & Tools: Python (heavy use), SQL (PostgreSQL), Bash, DockerLLMs: OpenAI, AnthropicPlatforms: Amazon Web Services (AWS)Frameworks & Libraries: LangChain, Hugging Face, PyTorchWorkflow Orchestration: (planned upgrades)Environments: Linux (server), macOS (local dev) Required Skills & Experience: 5+ years of hands-on experience as a data scientist or ML engineer, with demonstrated ownership of projects in production, and a minimum of 2 years’ experience with LLM’s.Proven experience applying LLMs and generative AI to real-world business problems.Strong Linux skills – comfortable navigating and scripting in a CLI-first environmentExpert Python skills – you write clean, maintainable, tested, and efficient codeDeep experience working with OpenAI models and APIs, including prompt engineering, finetuning and evaluationFluent in SQL with ability to work efficiently with PostgreSQL datasetsExperience using Docker for local and production developmentProficiency with LangChain for building multi-step LLM workflowsEffective remote communication and collaboration, especially in a distributed team with meetings on US Eastern TimeStrong business acumen—able to connect technical solutions to operational and client value.Startup-style drive, agility, and hands-on mindset—you ship, not just ideate.Creativity and experimentation—willing to try, fail, and improve.Exceptional communication skills—can explain complex ideas simply and persuasively. What We’re Looking For Proven experience applying LLMs and generative AI to real-world business problems.Deep proficiency in Python, NLP, and AI frameworks (e.g., Hugging Face, LangChain), vector databases, and prompt engineering.Strong business acumen—able to connect technical solutions to operational and client value.Startup-style drive, agility, and hands-on mindset—you ship, not just ideate.Creativity and experimentation—willing to try, fail, and improve.Exceptional communication skills—can explain complex ideas simply and persuasively.Minimum 3–5 years of experience in AI/ML roles, preferably in B2B or SaaS environments.Bachelor or Master in Computer Science, Data Science, AI, or related field. Nice to Have: Experience with AWS cloud services (EC2, S3, etc.)Familiarity with workflow orchestration toolsKnowledge of media analytics, journalism, or influence measurementPrior work with data labeling, theme detection, or benchmarking model output

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