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# Senior Data Scientist

- **Company:** The Battery
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Artificial Intelligence, Computer Vision, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Object Detection, Performance Tuning, SQL Databases, Cloud Platform System, Retrieval-Augmented Generation, Large Language Models, Deep Learning, Model Validation, Generative AI, Pyspark, Kubernetes, Data Analytics, Machine Learning Operations, Stream Processing, Docker, Network Optimization
- **Published:** November 6, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8iulvpnd

## About the Role

* 3+ years of strong hands-on experience in Python and SQL (PySpark preferred).
 * Proven experience in building ML models from scratch, including time-series forecasting, geospatial models, statistical modeling, and deep learning.
 * Practical, production-level experience with LLMs, RAG architectures, and modern AI tooling.
 * Hands-on exposure to Computer Vision models such as object detection, OCR, and facial recognition.
 * Experience deploying and maintaining models using Docker and cloud environments (Kubernetes exposure is a plus).
 * Strong understanding of real-time data processing frameworks and ML pipelines.
 * Demonstrated ability to solve complex, ambiguous problems in a fast-scaling startup environment.
 * Strong ownership mindset with experience leading and mentoring teams and collaborating cross-functionally.
 * Experience working with IoT and geospatial data is a plus.

## Description

We are looking for a Senior Data Scientist to drive Battery Smart's Data Science, Machine Learning, and Applied AI initiatives.

This is a senior Individual Contributor (IC) role that requires strong hands-on technical expertise and end-to-end ownership of critical business problems and AI initiatives. The individual will be responsible for identifying high-impact opportunities, designing and developing advanced ML/AI solutions, and taking them from experimentation to production.

The role will own key areas of the Data Science and Applied AI roadmap, build scalable and production-grade ML and AI systems, and work closely with Product, Engineering, Operations, and Leadership to translate complex business problems into impactful, data-driven solutions., * Own end-to-end data science and machine learning solutions across demand forecasting, fraud detection, underwriting, driver behavior analysis, and network optimization.

 * Design, build, deploy, and monitor time-series, geospatial, statistical, and real-time predictive models in production.
 * Drive Applied AI and GenAI initiatives, including:
 * LLM-based applications.
 * RAG (Retrieval-Augmented Generation) pipelines.
 * Embeddings, agent workflows, and decision-support systems.
 * Use cases such as call transcript analysis, operations intelligence, and automated insights.
 * Develop and implement Computer Vision solutions, including face recognition, OCR, misuse/fraud detection, and asset monitoring.
 * Take complete technical ownership of projects-from problem definition and data acquisition to model development, deployment, monitoring, and performance optimization.
 * Identify opportunities to leverage advanced analytics, machine learning, and AI to improve business outcomes, operational efficiency, and revenue.
 * Build scalable, reliable, and production-ready ML/AI pipelines and systems, ensuring model performance, reliability, and continuous improvement.
 * Work closely with Engineering teams to integrate ML/AI models into production applications and business workflows.
 * Collaborate with Product, Engineering, Operations, and Leadership to understand business challenges and translate ambiguous requirements into scalable AI-driven solutions.
 * Stay up to date with emerging developments in Machine Learning, Generative AI, and Applied AI, and evaluate their applicability to Battery Smart's business use cases.
 * Establish technical best practices around model development, experimentation, deployment, monitoring, and documentation.