Data Scientist

Lantern; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Lantern is seeking a hands‑on, client‑facing Senior Data Scientist to design, develop, and operationalize advanced analytics, ML, generative AI, and agentic AI solutions using Azure Databricks and the Microsoft AI ecosystem. You will partner with client stakeholders, data engineers, and application teams to translate business problems into secure, governed, scalable, and explainable AI solutions.

You will lead discovery sessions, perform data preparation and feature engineering, and build

Qualifications

• 5+ years of experience developing and delivering data science, machine learning, or AI solutions.
• Strong hands-on experience with Azure Databricks for data preparation, distributed model development, experiment tracking, model lifecycle management, and production deployment.
• Advanced proficiency in Python and SQL, with practical experience in PySpark and frameworks such as scikit‑learn, XGBoost, TensorFlow, or PyTorch.
• Strong foundation in statistics, supervised and unsupervised learning, feature engineering, model evaluation, explainability, and experimental design.
• Experience developing generative AI solutions using large language models, embeddings, vector databases, prompt engineering, evaluation, and agentic patterns.
• Working knowledge of Microsoft Azure AI Foundry, Azure OpenAI, Microsoft Fabric, OneLake, Power BI, and broader Azure data and AI ecosystem.
• Experience with MLOps or LLMOps, CI/CD, model serving and monitoring, data governance, Unity Catalog, security, responsible AI, performance, and cost optimization.
• Strong consulting, communication, visualization, documentation, problem-solving, and stakeholder-management skills, with the ability to explain complex models to technical and executive audiences.

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.
• Implement MLOps and LLMOps practices including source control, automated testing, CI/CD, model registration, deployment, monitoring, drift detection, responsible AI, and cost optimization.
• Communicate findings and model behavior through clear visualizations, executive‑ready narratives, demonstrations, and technical documentation.
• Own assigned workstreams, manage risks and dependencies, and collaborate with client teams to drive adoption and measurable business outcomes.
• Contribute to proposals, reusable accelerators, technical standards, peer reviews, mentoring, and the growth of Lantern’s Databricks and Microsoft AI practices.

Skills

Azure Databricks

Python

SQL

PySpark

Machine Learning

Generative AI

MLOps

Data Visualization

Communication

Tools

Delta Lake

Unity Catalog

MLflow

Power BI

Azure OpenAI

Microsoft Fabric

Job description

AtLantern, 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.
• Implement MLOps and LLMOps practices including source control, automated testing, CI/CD, model registration, deployment, monitoring, drift detection, responsible AI, and cost optimization.
• Communicate findings and model behavior through clear visualizations, executive‑ready narratives, demonstrations, and technical documentation.
• Own assigned workstreams, manage risks and dependencies, and collaborate with client teams to drive adoption and measurable business outcomes.
• Contribute to proposals, reusable accelerators, technical standards, peer reviews, mentoring, and the growth of Lantern’s Databricks and Microsoft AI practices.

Skills, Knowledge and Expertise

• 5+ years of experience developing and delivering data science, machine learning, or AI solutions, preferably in consulting or other client‑facing environments.
• Strong hands‑on experience with Azure Databricks for data preparation, distributed model development, experiment tracking, model lifecycle management, and production deployment.
• Advanced proficiency in Python and SQL, with practical experience in PySpark and common data science frameworks such as scikit‑learn, XGBoost, TensorFlow, or PyTorch.
• Strong foundation in statistics, supervised and unsupervised learning, feature engineering, model evaluation, explainability, and experimental design.
• Experience developing generative AI solutions using large language models, retrieval‑augmented generation, embeddings, vector databases, prompt engineering, evaluation, and agentic patterns.
• Working knowledge of Microsoft Azure AI Foundry, Azure OpenAI, Microsoft Fabric, OneLake, Power BI, and the broader Azure data and AI ecosystem.
• Experience with MLOps or LLMOps, CI/CD, model serving and monitoring, data governance, Unity Catalog, security, responsible AI, performance, and cost optimization.
• Strong consulting, communication, visualization, documentation, problem‑solving, and stakeholder‑management skills, with the ability to explain complex models to technical and executive audiences.

Preferred Certifications and Credentials

• Databricks Certified Machine Learning Professional or Machine Learning Associate
• Databricks Certified Data Engineer Associate or Professional
• Databricks Solutions Architect Champion is highly preferred and considered a strong differentiator

Voluntary Self‑Identification

For government reporting purposes, we ask candidates to respond to the below self‑identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Lantern’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.

A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.