The Data Scientist, D&T will be part of a multidisciplinary team responsible for designing and developing innovative data-driven analytical solutions. This role will leverage advanced analytics, Machine Learning, NLP, Computer Vision, and Generative AI to address complex business challenges and deliver measurable value.
Essential Duties and Responsibilities
Partner with stakeholders across functions to uncover and prioritize use cases where ML, statistical modeling, or GenAI/Agentic AI solutions can create business impact.
Lead end-to-end model/agent lifecycles: from problem definition, data exploration, feature engineering, and model/agent design to deployment, monitoring, and continuous improvement.
Ingest, integrate, and preprocess large-scale structured, semi-structured, and unstructured datasets, ensuring high standards of data quality and integrity.
Develop and enhance scalable data pipelines and infrastructure; proactively detect and mitigate data drift, bias, or quality gaps.
Drive development of specialized computer vision solutions (e.g., object detection, classification, OCR, segmentation) for business-critical applications such as manufacturing, quality control, and compliance monitoring
Design and operationalize CI/CD and AgentOps workflows: model/dataset versioning, reproducibility, automated testing, deployment, rollback, and governance.
Define, implement, and monitor evaluation metrics (accuracy, robustness, fairness, latency, safety, etc.) for both offline and production environments.
Conduct error analysis, monitor live model/agent performance, and ensure compliance with AI governance and ethical standards.
Create intuitive dashboards, reports, and data visualizations (e.g., Power BI, Fabric) to communicate insights to technical and non-technical stakeholders.
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Translate technical findings into actionable business recommendations; clearly communicate risks, performance, and opportunities to decision-makers.
Collaborate closely with BI, engineering, and domain experts to operationalize data-driven solutions at scale.
Awareness of compliance, SOPs, and ethical AI practices in enterprise environments.
Working knowledge of CI/CD, MLOps and AgentOps practices: reproducible pipelines, monitoring, governance with telemetry and observability.
Education
Bachelor's or master's degree in computer science, Mathematics, Statistics, Data Science, or related quantitative field.
Work Experience
3 - 6 years of relevant experience in data science, machine learning, or applied AI roles.
Preferred Knowledge, Skills and Abilities
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Strong proficiency in Python, SQL and prompt engineering for data manipulation, analysis, and querying large datasets.
Context engineering and proficiency in executing GenAI projects at scale with prompt versioning, evaluation and tracing to debug GenAI pipelines
Proficiency with Computer Vision libraries and frameworks (e.g., OpenCV, TensorFlow, PyTorch, StableDiffusion) and experience in building real-world image/video analysis pipelines.
Familiarity with Generative AI and LLMs, including experience building Agentic-RAG pipelines using frameworks such as ReAct with tool integrations, memory, and reflection
Solid understanding of how to evaluate/test ML & AI models: accuracy, robustness, fairness, drift, latency, interpretability, and safety.
Exposure in building ETL pipelines and advanced feature engineering workflows for ML/AI, including vision-based applications
Strong foundation in statistics: regression, hypothesis testing, probability distributions
Independent problem-solving skills, creativity, and the ability to prioritize in fast-paced environments.
Strong collaboration and communication skills, with the ability to work effectively in global and virtual settings.
Familiarity with cloud platforms (Azure preferred, including Azure AI Foundry, AzureML, OpenAI platform, Synapse and storage).
Skilled in data visualization and BI tools (Power BI or equivalent), with the ability to present complex insights clearly to non-technical stakeholders.
Agentic frameworks like lanGraph, AutoGen, CrewAI etc. familiar with implementing graph RAG, multimodal RAG
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Travel Requirements
10%: Up to 26 business days per year
Physical Requirements
Sedentary-Exerting up to 10lbs/4kgs of force occasionally, and/or negligible amount of force frequently or constantly to lift, carry, push, pull, or otherwise move objects, including the human body. Sedentary work involves sitting most of the time.
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