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# Data Scientist

- **Company:** M&BS, LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Python (Programming Language), Machine Learning, Automation of Marketing, Performance Tuning, Tensorflow, Azure Machine Learning, SQL Databases, Feature Engineering, Chatbots, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Scikit Learn, Kubernetes, Information Technology, Xgboost, Machine Learning Operations, Virtual Agents, Docker
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecip05li5

## About the Role

* Bachelor's degree in Mathematics, Computer Science, IT, Econometrics or related fields.
 * 2+ years of experience as a Data Scientist or AI Engineer.
 * Strong knowledge of Statistics, Machine Learning and Predictive Modeling.
 * Proficiency in Python, SQL and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch/TensorFlow.
 * Experience with MLOps: MLflow, Airflow/Prefect, Docker, MinIO and model deployment.
 * Knowledge/experience with LLMs, RAG, Prompt Engineering, LangChain/LlamaIndex/LangGraph is a strong advantage.
 * Knowledge of Apache Spark, Kubernetes and AI Agent development is a plus.
 * Experience in Finance, Securities or Banking is preferred.
 * Strong analytical, problem-solving and Product Mindset.
 * TOEIC 500 or IELTS 5.5

 3. Preferred Qualifications
 * Experience building AI Agents / Agentic Workflows.
 * Experience developing AutoML / internal ML platforms.
 * Experience integrating AI with CRM, Marketing Automation or CDP.
 * Experience with OpenAI, Claude, Gemini and fine-tuning techniques such as LoRA/QLoRA/PEFT.
 * Knowledge of Securities products, investor behavior and KYC/AML.

## Description

a. ML Platform Development & Operations

 * Deploy and operate ML Platform systems, including data ingestion, feature engineering, model training and serving.
 * Build and maintain automated ML pipelines using Prefect/Airflow and MLflow.
 * Package models with Docker, deploy to production and monitor model performance/drift.

b. Business Forecasting & Predictive Modeling

 * Develop Churn Models to identify customers at risk of becoming inactive.
 * Build Propensity Models to predict customer behaviors and optimize conversion rates.
 * Perform Customer Segmentation to support personalized marketing campaigns.

c. AI Applications & Chatbot Development

 * Apply RAG and Prompt Engineering to improve chatbots and internal AI assistants.
 * Develop Agentic Workflows to automate and optimize business processes.
 * Integrate AI into CRM systems to enhance customer management and personalization.
 * Optimize chatbot processing and response logic to improve customer interactions.


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