Data Scientist
Job in
Germany, Pike County, Ohio, USA
Listed on 2026-01-12
Listing for:
Rulesiq
Full Time
position Listed on 2026-01-12
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, AI Engineer, Data Engineer, Cloud Computing
Job Description & How to Apply Below
Role Summary
We are seeking a highly skilled and versatile Data Scientist/Machine Learning Engineer to join our team. The ideal candidate will have a strong foundation in machine learning, data science, and software engineering, coupled with the ability to design and implement end-to-end systems. This role involves working with cutting-edge technologies, including LLMs, recommendation models, and NLP, while leveraging big data engineering, system design, and cloud infrastructure to deliver impactful solutions.
Key Responsibilities- Develop and deploy machine learning models for various use cases such as recommendation systems, propensity scoring, and NLP.
- Design, train, and fine-tune large language models (LLMs) and integrate them into production workflows.
- Conduct exploratory data analysis (EDA), feature engineering, and statistical modeling to derive actionable insights.
- Build and optimize data pipelines and workflows for large-scale data processing using tools like Apache Spark, EMR, or similar.
- Collaborate with the data engineering team to ensure data integrity, scalability, and efficiency.
- Architect and implement end-to-end ML systems, from data ingestion to model deployment and monitoring.
- Develop robust and scalable APIs for model integration and data access.
- Ensure seamless integration with backend systems (Mongo
DB) and cloud infrastructure (AWS).
- Containerize applications and ML models using Docker, ensuring portability and consistency across environments.
- Orchestrate and manage deployments using Kubernetes.
- Monitor and optimize system performance, ensuring high availability and reliability.
- Utilize AWS services such as S3, Lambda, Sage Maker, and ECS for building and deploying solutions.
- Design efficient and scalable data storage solutions using Mongo
DB and related tools.
- Work closely with cross-functional teams, including data engineers, software developers, and product managers.
- Translate business requirements into technical solutions.
- Proficiency in Python, with expertise in libraries such as Num Py, Pandas, Scikit-learn, Tensor Flow, PyTorch, and Hugging Face Transformers.
- Strong understanding of machine learning algorithms, deep learning architectures, and NLP techniques.
- Hands-on experience with recommendation systems, propensity scoring, and statistical methods.
- Knowledge of big data tools (e.g., Spark, Hadoop) and stream processing.
- Solid experience with API development and integration.
- Expertise in Docker, Kubernetes, and CI/CD practices.
- Familiarity with AWS services and cloud-native architectures.
- Strong grasp of data science concepts, including predictive modeling, clustering, and classification.
- Experience with LLM fine-tuning and deployment for NLP applications.
- Sound understanding of system design principles and infrastructure best practices.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- 3+ years of professional experience in machine learning engineering or data science roles.
- Previous experience in building and deploying end-to-end ML pipelines in production environments.
- Experience with Mongo
DB Atlas and serverless architectures. - Knowledge of MLOps tools and practices for product ionizing ML models.
- Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana).
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