Senior Data Scientist
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Key skills for this role
About the Role
Cander is seeking a Senior Data Scientist to lead AI initiatives for defense applications, developing generative AI, NLP, and predictive models. The role requires 5+ years experience, expert Python skills, and deep experience with transformer-based LLMs.
Key Skills for This Role
Responsibilities
- Lead the development and deployment of generative AI and NLP solutions for engineering applications
- Design, fine tune, and deploy Large Language Models (LLMs) to interpret complex regulatory texts
- Convert interpreted regulatory content into computer processable formats for automated compliance checking
- Architect NLP driven methods to map natural language requirements to metadata entities
- Implement Retrieval Augmented Generation (RAG) pipelines for high accuracy querying of technical documentation
- Develop time series forecasting models to predict spend categories and material demand
- Build machine learning classifiers to categorize supplier risks and operational anomalies
- Design and oversee robust data extraction pipelines from various sources
- Collaborate with backend engineers to integrate AI models into compliance and risk engines
- Optimize model performance to handle large scale datasets and high volume processing
- Validate model outputs against test cases and historical data, debugging false positives/negatives
Requirements
- 5+ years of experience in Data Science or Machine Learning, with a proven track record of deploying models into production environments
- Expert proficiency in Python and standard ML libraries, including TensorFlow, PyTorch, Scikit learn, Pandas, and NumPy
- Deep experience with transformer based models (GPT, BERT, Llama) and prompt engineering techniques
- Strong grasp of both supervised and unsupervised learning techniques
- Proficiency in handling complex data structures (JSON, XML) and familiarity with database querying (SQL/NoSQL) or graph data structures
- Experience with data extraction from specialized formats
- Understanding of how to expose models via RESTful APIs (Flask/FastAPI) and integrate them into larger software architectures
- Solid understanding of statistics, probability distributions, and A/B testing
- Ability to quickly grasp complex domain terminology and translate them into logical workflows
- Experience working in structured delivery models such as Agile or Sprint based frameworks
- Strong communication skills to collaborate effectively with Domain Experts, Backend Engineers, and Product Managers
Full Job Posting
Job Summary
- We are seeking a Senior Data Scientist to lead the technical development and deployment of high impact AI initiatives for advanced defense capabilities. You will transition from exploratory modeling to building production grade AI systems that directly enhance design, manufacturing, and procurement
Key Responsibilities
- Lead the development and deployment of generative AI and NLP solutions for engineering applications within the platform.
- Design, fine tune, and deploy Large Language Models (LLMs) to interpret complex regulatory texts such as building codes and military standards.
- Convert interpreted regulatory content into computer processable formats (e.g., object property condition value tuples) to enable execution by downstream compliance engines.
- Architect NLP driven methods to map natural language requirements directly to metadata entities across various schemas.
- Implement Retrieval Augmented Generation (RAG) pipelines to enable high accuracy querying of technical documentation and historical project data.
- Develop time series forecasting models to predict spend categories and material demand by integrating internal ERP data with external macroeconomic signals.
- Build machine learning classifiers to categorize supplier risks and operational anomalies.
- Design and oversee robust data extraction pipelines to transform raw data from Data Lakehouse environments, external web sources, SAP databases, and other systems.
- Collaborate with backend engineers to integrate AI models into cohesive compliance and risk engines.
- Optimize model performance to handle large scale datasets and high volume processing within operational timeframes.
- Validate model outputs against test cases and historical data, debugging false positives/negatives to ensure defense grade reliability.
Qualifications And Requirements
- 5+ years of experience in Data Science or Machine Learning, with a proven track record of deploying models into production environments.
- Expert proficiency in Python and standard ML libraries, including TensorFlow, PyTorch, Scikit learn, Pandas, and NumPy.
- Deep experience with transformer based models (GPT, BERT, Llama) and prompt engineering techniques such as few shot learning and fine tuning.
- Strong grasp of both supervised and unsupervised learning techniques.
- Proficiency in handling complex data structures (JSON, XML) and familiarity with database querying (SQL/NoSQL) or graph data structures.
- Experience with data extraction from specialized formats, including structured and unstructured sources.
- Understanding of how to expose models via RESTful APIs (Flask/FastAPI) and integrate them into larger software architectures.
- Solid understanding of statistics, probability distributions, and A/B testing.
- Ability to quickly grasp complex domain terminology and translate them into logical workflows.
- Experience working in structured delivery models such as Agile or Sprint based frameworks.
- Strong communication skills to collaborate effectively with Domain Experts, Backend Engineers, and Product Managers.
Technical Skills
- Expert proficiency in Python and standard machine learning libraries, including TensorFlow, PyTorch, Scikit learn, Pandas, and NumPy.
- Deep experience with transformer based large language models (GPT, BERT, Llama) and advanced prompt engineering techniques.
- Proficiency in handling complex data structures (JSON, XML) and querying databases using SQL/NoSQL.
- Understanding of backend systems and ability to expose AI models via RESTful APIs using Flask or FastAPI.
- Solid foundation in statistics, probability distributions, and A/B testing.
- Experience designing and implementing Retrieval Augmented Generation (RAG) pipelines.
- Familiarity with data extraction pipelines to transform raw data from various sources.
- Knowledge of model orchestration and optimization techniques.
- Ability to validate model outputs against test cases and historical data.
Location and Work Environment
- Primary Location: Abu Dhabi, United Arab Emirates
- Work Setting: Hybrid or on site collaboration with cross functional teams
- Delivery Model: Structured 'Sprint Zero' to 'Stage Gate' framework
Company And Project Focus
- Join a dynamic organization where innovation and data driven decision making are at the core of our mission. You will contribute to high impact projects focused on leveraging advanced analytics, machine learning, and statistical modeling to solve complex business challenges.
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