AIML Data Scientist
AIML Data Scientist
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Job Description
Job Title: AI/ML Data Scientist
Location: Remote
Job Overview:
We are seeking a highly skilled AI/ML Data Scientist to join our team and contribute to innovative solutions across diverse business and technical domains. In this role you will develop deploy and optimize machine learning models working with largescale datasets and advanced analytics to drive business insights. You will be part of a dynamic team collaborating with product managers engineers and customers to tackle complex challenges in fields like supply chain optimization physical system design and network analysis.
Key Responsibilities:
- Data Analysis & Model Development: Conduct sophisticated data mining predictive modeling and statistical analyses to uncover insights from largescale structured and unstructured datasets.
- Machine Learning Solutions: Design and develop machine learning models for realworld applications like recommendation systems network dynamics analysis and system performance prediction.
- MLOps & Automation: Partner with data engineers to refactor workflows and implement highly automated MLOpsbased processes for streamlined model deployment and monitoring.
- Graph & Network Modeling: Build models to understand complex network behaviors supply chain dynamics and emergent patterns in large datasets. Develop metrics and models to describe and predict network performance.
- Performance Optimization: Optimize the performance and scalability of machine learning models applying techniques such as numerical optimization simulations and model finetuning.
- Collaboration & Communication: Work crossfunctionally with data engineers product managers and other stakeholders to ensure seamless integration of models into business applications. Communicate technical results to both technical and nontechnical audiences.
- Research & Innovation: Stay at the forefront of AI/ML advancements exploring new techniques in areas such as physicsinformed neural networks (INNs) large language models (LLMs) and generative models to enhance our AI capabilities.
Required Skills & Qualifications:
- Education: BS MS or PhD in Computer Science Data Science Physics Applied Mathematics or related fields.
- Machine Learning Expertise: Strong experience in machine learning frameworks such as TensorFlow PyTorch or other relevant platforms. Proven expertise in developing and deploying machine learning models at scale.
- Data Science Tools: Proficiency in Python NumPy SQL and data visualization tools such as Tableau. Familiarity with cloud platforms (AWS Azure Databricks) and opensource technologies like Kafka Beam and Neo4j.
- MLOps & CI/CD: Handson experience with MLOps pipelines CI/CD tools (GitLab Argo Harness) and containerization (Docker Kubernetes).
- Network & Graph Analysis: Strong understanding of graph mining network analysis and techniques for modeling network dependencies and resilience metrics.
- Statistical Analysis & Optimization: Indepth knowledge of statistical techniques simulations and numerical optimization to improve the performance of models.
- Communication Skills: Ability to explain complex technical findings to diverse audiences ranging from data engineers to nontechnical stakeholders.
Nice to Have:
- Experience with LLM models finetuning RLHF and generative models.
- Expertise in observability and monitoring tools like Grafana LOKI and EFK.
- Previous experience with supply chain analytics or network analysis in industries such as ecommerce banking or insurance.
Employment Type
Full Time
