Data Scientist

At Lantern, our company culture stands as the bedrock of our success and a source of pride for our teams. We firmly believe that a culture founded on trust forms the basis for enduring relationships with clients, colleagues, and partners.

Within this culture, we nurture an environment of respect, inclusion, and belonging, fostering collaboration among inspired teams. We prioritize the well-being of our colleagues, the success of our clients, and our positive impact on society.
Embracing a growth mindset where curiosity thrives, we celebrate excellence and value individuals who inspire and mentor others, elevating the collective. Our driving force lies in personal and business growth. We go above and beyond to surprise and delight our clients, delivering tangible business value. In facing challenges, we make tough choices and solve complex problems to positively influence our clients, their customers, and the world at large.
As a Microsoft services partner, we hold ourselves to the highest standards of technical excellence. This commitment to quality is evident not only in our work but also in how we support and empower our employees. At Lantern, our culture mirrors our core values and unwavering dedication to realizing our purpose and vision, making it a dynamic and fulfilling workplace. Together, we transcend the ordinary and achieve extraordinary results.

Lantern is seeking a hands-on, client-facing Senior Data Scientist to design, develop, and operationalize advanced analytics, machine learning, generative AI, and agentic AI solutions using Azure Databricks and the Microsoft data and AI ecosystem. You will partner with client stakeholders, data engineers, architects, and application teams to translate business problems into secure, governed, scalable, and explainable AI solutions - from experimentation and feature engineering through deployment, monitoring, and measurable adoption. 

Key Responsibilities

• Lead discovery sessions to define analytical problems, success metrics, data requirements, experimentation plans, and production roadmaps. 
• Explore and prepare structured and unstructured data; perform feature engineering, statistical analysis, and model selection using Python, SQL, Spark, and Databricks notebooks. 
• Build, evaluate, and tune predictive, forecasting, optimization, natural language processing, computer vision, generative AI, and agentic AI solutions. 
• Use Azure Databricks capabilities such as Delta Lake, Unity Catalog, MLflow, Feature Engineering, Model Serving, Mosaic AI, and vector search to create governed, production-ready solutions. 
• Integrate solutions with Microsoft Azure AI Foundry, Azure OpenAI, Microsoft Fabric, OneLake, Power BI, and Azure services as appropriate.