The primary responsibilities of this role are to:

Solve real agricultural problems using deep learning and AI across image and other data modalities, translating complex models into tangible business and scientific impact.

Design and implement end-to-end machine learning pipelines for computer vision use cases, including segmentation, classification, detection, and multi-task learning.

Prototype, evaluate, and iterate on cutting-edge architectures such as CNNs, Vision Transformers, foundational and large-scale vision models, ensuring state-of-the-art performance.

Optimize models for accuracy, robustness, and inference efficiency, including experimentation with hyperparameters, compression, and deployment-oriented optimisations.

Independently build scalable data pipelines for training, validation, and evaluation, including data ingestion, augmentation strategies, and active learning loops.

Collaborate cross-functionally with product, data, and software engineering teams to integrate models into production systems and deliver reliable, maintainable solutions.

Contribute to MLOps practices, including model versioning, deployment, monitoring, and retraining workflows using modern tooling and cloud-based platforms.

Build strong cross-functional relationships and actively engage with the broader Data Science Community to share best practices, align on standards, and co-create innovative solutions.

Present clear, compelling, and validated stories about experiments, results, and recommendations to peers, senior management, and internal customers to drive strategic and operational decisions.

We seek an incumbent who possesses the following:

M.S. with 2+ years of experience or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on machine learning or computer vision.

Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow.

Hands-on experience with modern computer vision architectures including models such as ResNet, UNet, DeepLab, YOLO, SegFormer, SAM, and Vision Transformers.

Strong background in handling large-scale datasets and creating custom datasets, for example using frameworks such as Hugging Face Datasets.

Solid understanding of core machine learning concepts including loss functions, regularization, optimisation, and learning rate scheduling.

Experience developing and deploying models using cloud-based ML platforms such as AWS SageMaker.

Familiarity with Unix environments, including bash, file systems, and core utilities.

Strong engineering practices including use of Git, Docker, CI/CD pipelines, modular codebase design, and unit testing.

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This role operates at the intersection of digital operations, customer experience, and AI-powered transformation. You will help drive the integration of intelligent automation, predictive analytics, and GenAI capabilities into digital service channels to improve customer experiences, enhance agent efficiency, and optimize operational performance.

Key Responsibilities

• Identify and scope opportunities to utilize AI, machine learning, and automation to optimize digital experience operations and agent support processes.
• Collaborate with product owners to build AI-informed business cases, including ROI modeling for predictive experiences, intelligent routing, and automated troubleshooting.
• Manage AI-enabled dashboards and monitoring systems that surface real-time anomalies, experience dips, and emerging performance trends.
• Partner with CX, analytics, and engineering teams to run A/B tests leveraging AI-generated variants, measuring uplift and customer impact.
• Translate customer and agent insights using AI-powered analytics (e.g., text/sentiment analysis, pattern detection) into actionable recommendations for journey improvements.
• Apply GenAI capabilities to improve team operations, e.g., automated insights summaries, triaging, root cause analysis drafting, and workflow documentation.

Experience & Education Requirements

• Overall experience > 6-8 years, 4+ years’ experience required with extensive relevant customer understanding/user research/consulting experience, packaging and delivering insights to influence change. 4+ years of combined experience required in analytics, performance reporting, and/or process improvement.
• Advanced project and process management experience. Agile preferred.
• Bachelor's degree preferred in Technology, Mathematics, Statistics, Business, or related field.
• Master’s degree preferred in Management, Analytics, Artificial Intelligence.
• Experience working with AI/ML-driven platforms or analytics tools (e.g., customer behavioral modeling, NLP pipelines, predictive analytics).
• Background or coursework in AI, machine learning, data science, or human-centered AI preferred.
• Demonstrated ability to translate technical AI concepts into business language for non-technical stakeholders.
• Availability to work in PST time zone.

Other Critical Skills

• Familiarity with GenAI tools, conversational AI platforms, and AI-assisted productivity solutions.
• Ability to interpret outputs from models using techniques such as anomaly detection, clustering, and predictive scoring.
• Strong understanding of AI ethics, governance, and responsible AI frameworks.
• Comfortable working in environments where AI-driven decision automation informs prioritization and operational strategies.
• Possesses strong technical aptitude. Intermediate knowledge in using analytic tools such as Tableau and Microsoft Excel. Proficient in Microsoft Office including MS Word, Excel, Outlook, PowerPoint.
• Strong verbal communication and listening skills. Strong business acumen, with effective written and verbal communication skills.
• Ability to communicate, influence, and deliver with cross-functional teams and enterprise stakeholders. Ability to manage multiple projects with tight deadlines effectively with cross functional teams.

Software / Tool Skills

• Experience with AI/ML or data intelligence platforms (e.g., Azure ML, AWS SageMaker, Google Vertex AI—basic exposure acceptable).
• Hands-on familiarity with GenAI copilots, prompt engineering concepts, or LLM-based experience analysis tools.
• Experience interpreting insights from NLP, AI-powered text analytics, or conversational AI systems.
• Hands on experience with user Feedback/Data analysis tools – Qualtrics, Fullstory, Mixpanel etc.
• Good proficiency or practical experience of A/B Testing tools.
• Agile tools such as Jira, Rally etc.
• Understanding of Contact center and CMS tools.
• Excel - Intermediate/Advanced. Proficiency in Microsoft 365
• Power BI (Highly Preferred)

Requirements

• CX Operations
• Audit & Governance
• Data Analysis
• Insights & Predictive Analytics
• Root Cause Analysis
• Digital recommendations
• Competitive Analysis
• Personalization
• Agile framework

Benefits

• Competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Pension Plan
8. Paid Time Off
9. Training & Development

Note: Benefits differ based on employee level.

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As a FBS Senior Operations Analyst at Capgemini, you will play a key role in driving the integration of intelligent automation, predictive analytics, and GenAI capabilities into digital service channels to improve customer experiences, enhance agent efficiency, and optimize operational performance.

Role Description

This role operates at the intersection of digital operations, customer experience, and AI-powered transformation. You will help drive the integration of intelligent automation, predictive analytics, and GenAI capabilities into digital service channels to improve customer experiences, enhance agent efficiency, and optimize operational performance.

Key Responsibilities

• Oversee end-to-end digital service operations across customer and agent journeys, partnering with Product, Technology, and Architecture teams to ensure smooth delivery of features, fixes, and enhancements.
• Define and monitor KPIs such as experience scores, CSAT, FCR, and system uptime to track digital performance across various digital channels.
• Drive real-time customer and agent experience tracking, identify friction points, and lead UX improvement initiatives backed by data analysis and user feedback.
• Manage critical defects and high-priority escalations by coordinating with stakeholder teams to ensure rapid and accurate resolution.
• Build and maintain real-time dashboards to surface trends, generate insights, and inform leadership decisions; leverage tools such as Qualtrics, Mixpanel, and Fullstory etc.
• Use customer and partner research to strengthen analytical capabilities, identify market trends, and recommend customer experience enhancements.
• Partner with data science, analytics, and engineering teams to embed AI-driven insights into digital operations, enabling proactive issue detection and resolution.
• Apply AI-based predictive models to forecast demand, detect patterns, and inform operational and resource planning.
• Evaluate and operationalize AI copilots, GenAI assistants, and automation tools to streamline agent workflows and improve customer self-service.
• Promote responsible AI through governance, transparency, bias monitoring, explainability, and data privacy practices.
• Lead GenAI-powered experiments that include personalized content, conversational experiences, and journey-level optimizations.
• Support AI-driven journey analytics using NLP, clustering, sentiment analysis, and behavioral modeling to improve customer understanding.

Experience & Education Requirements

• Overall experience > 6-8 years, 4+ years’ experience required with extensive relevant customer understanding/user research/consulting experience, packaging and delivering insights to influence change. 4+ years of combined experience required in analytics, performance reporting, and/or process improvement.
• Advanced project and process management experience. Agile preferred.
• Bachelor's degree preferred in Technology, Mathematics, Statistics, Business, or related field.
• Master’s degree preferred in Management, Analytics, Artificial Intelligence.
• Experience working with AI/ML-driven platforms or analytics tools (e.g., customer behavioral modeling, NLP pipelines, predictive analytics).
• Background or coursework in AI, machine learning, data science, or human-centered AI preferred.
• Demonstrated ability to translate technical AI concepts into business language for non-technical stakeholders.
• Availability to work in PST time zone.

Other Critical Skills

• Familiarity with GenAI tools, conversational AI platforms, and AI-assisted productivity solutions.
• Ability to interpret outputs from models using techniques such as anomaly detection, clustering, and predictive scoring.
• Strong understanding of AI ethics, governance, and responsible AI frameworks.
• Comfortable working in environments where AI-driven decision automation informs prioritization and operational strategies.
• Possesses strong technical aptitude. Intermediate knowledge in using analytic tools such as Tableau and Microsoft Excel. Proficient in Microsoft Office including MS Word, Excel, Outlook, PowerPoint.
• Strong verbal communication and listening skills. Strong business acumen, with effective written and verbal communication skills.
• Ability to communicate, influence, and deliver with cross-functional teams and enterprise stakeholders. Ability to manage multiple projects with tight deadlines effectively with cross functional teams.

Software / Tool Skills

• Experience with AI/ML or data intelligence platforms (e.g., Azure ML, AWS SageMaker, Google Vertex AI—basic exposure acceptable).
• Hands-on familiarity with GenAI copilots, prompt engineering concepts, or LLM-based experience analysis tools.
• Experience interpreting insights from NLP, AI-powered text analytics, or conversational AI systems.
• Hands on experience with user Feedback/Data analysis tools – Qualtrics, Fullstory, Mixpanel etc.
• Good proficiency or practical experience of A/B Testing tools.
• Agile tools such as Jira, Rally etc.
• Understanding of Contact center and CMS tools.
• Excel - Intermediate/Advanced. Proficiency in Microsoft 365
• Power BI (Highly Preferred)

Requirements

• Optimization Testing (A/B Testing)
• Multivariate testing
• Personalization
• Digital Workflow optimization
• Stakeholder collaboration

Benefits

• Competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses
2. Comprehensive benefits package
3. Career development and training opportunities
4. Flexible work arrangements (remote and/or office-based)
5. Dynamic and inclusive work culture within a globally renowned group
6. Private Health Insurance
7. Pension Plan
8. Paid Time Off
9. Training & Development

Note: Benefits differ based on employee level.

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