Senior Data Scientist

About Constellation: Constellation is a cutting-edge AI solution that empowers highly regulated and complex industries with the insights and content they need to fuel their business. Specializing in industries such as healthcare, automotive, insurance, and finance, our powerful data/AI insights tools inform the creation of compliant content at scale. We enable our customers to harness their data and streamline the creation of localized, personalized content. A global, NYC-based company, Constellation has been revolutionizing marketing technology and data intelligence in order to drive exponential growth since its founding in 2016. Constellation was named the 65th Fastest-Growing Private Company in America, the 10th Fastest-Growing Women-Owned Private Company, and the 7th Fastest-Growing Marketing & Advertising Company by Inc 500. In 2022, our platform won the Digiday Technology Award for Best Marketing Automation Platform. About The Role We're looking for a Senior Data Scientist to take a leading role in building the AI that powers Constellation. You'll ship production models—generative AI, autonomous agents, and predictive models for churn, LTV, and pricing— while mentoring a growing team and shaping our technical standards. If you want your work to reach real users in regulated industries like automotive and life sciences (not sit in a notebook), this is that role. What You’ll Do Lead AI/ML Initiatives: Architect, prototype, and productionize ML models, including generative AI, recommendation systems, and domain-specific agents tailored to marketing, regulatory compliance, and creative workflows. Drive Agentic AI Capabilities: Build agent-based systems that reason, retrieve, validate, and act autonomously, supporting prompt chaining, tool usage, and evaluation feedback loops. Mentor & Scale the Team: Coach junior and mid-level data scientists and engineers, review code, drive standards, and help shape a culture of high performance, curiosity, and inclusivity. Collaborate Cross-Functionally: Work closely with Product, Engineering, Design, and GTM teams to integrate intelligent systems into customer-facing features and internal tooling. Model Business-Critical Outcomes: Develop models for customer LTV, churn, content efficacy, user engagement, and pricing optimizations, leveraging both structured and unstructured data. Own the ML Stack: Contribute to architecture decisions on model lifecycle management, pipelines, monitoring, and experiment tracking using modern tooling like MLflow, SageMaker, or Vertex AI. Drive Applied Research: Stay on top of advances in transformers, large language models, retrieval-augmented generation, and probabilistic programming—and bring these innovations to production. What We’re Looking For 8+ years of experience in data science, ML engineering, or applied AI, with a track record of shipping models in production. Deep experience with Python (Pandas, NumPy, Scikit-learn) and modern ML/DL libraries (PyTorch, TensorFlow, Hugging Face, LangChain). Strong command of SQL and data modeling in cloud warehouses (e.g., Snowflake, BigQuery, Redshift). Experience building systems using AWS (Lambda, SageMaker, EC2, Batch, S3) or similar cloud platforms. Solid understanding of ETL/data pipelines and orchestration tools (e.g., Airflow). Experience with agent-based architectures, LLMs, and real-world generative AI applications (NLP, content synthesis, summarization, retrieval). Familiarity with automotive or life sciences data domains is a strong plus—whether in marketing analytics, medical devices, vehicle inventory intelligence, or regulatory content. Outstanding communication and mentorship skills, with a collaborative mindset and a passion for helping others grow. Bonus Experience Experience with probabilistic modeling (e.g., PyMC3, Stan). Familiarity with graph databases (e.g., Neo4j) and modeling network effects. Prior exposure to recommendation engines, survival models, or multi-touch attribution. Experien…