Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

Senior Data Scientist, Finance

We are seeking a Senior Data Scientist to lead high-impact, data-driven initiatives that advance predictive techniques and accelerate decision-making across the organization. This role emphasizes Generative AI (GenAI) and applied machine learning supported by a strong foundation in modern data engineering. The ideal candidate combines scientific rigor with creativity, capable of transforming complex datasets into predictive insights and intelligent agents that directly influence business strategy.

Key Responsibilities

Predictive Modeling & Forecasting

Design, develop, and improve time series models to forecast revenue, customer usage, and renewal rates across customer segments.
Translate manual forecasting processes into scalable, auditable machine learning models that ensure interpretability, accuracy, and compliance.

Generative AI

Build and optimize AI agents in AWS Bedrock to augment finance members’ workstreams to accelerate tasks related to revenue, bookings, and expenses.
Apply prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) to extend and improve existing agentic systems.
Implement guardrails, compliance filters, and content moderation layers to ensure security and SOX-compliant AI operations.

Data Engineering & Feature Development

Contribute to the migration and expansion of existing data pipelines into a new architecture that empowers the team’s centralized data initiatives.
Design and deploy feature engineering frameworks to capture temporal, behavioral, and financial signals critical for forecasting accuracy.

Operationalization & Model Lifecycle

Implement MLOps best practices for model deployment, versioning, monitoring, and retraining across production environments.
Contribute to documentation, reproducibility, and governance standards to ensure reliable, auditable, and compliant AI systems.

Cross-Functional Collaboration

Partner with finance, IT, and operations teams to align data science solutions with business objectives.
Translate complex machine learning outcomes into actionable insights and compelling narratives for both technical and non-technical audiences.

Key Qualifications

4+ years of experience in data science or applied ML, with at least 1 year focused on LLM/GenAI applications.
Proven expertise in time series forecasting, predictive modeling, and statistical analysis.
Advanced proficiency in Python, SQL, and ML libraries such as scikit-learn.
Hands-on experience automating data and analysis workflows in Python, from ingestion and feature generation to reporting and deployment.
Strong understanding of MLOps tools and cloud platforms (preferably AWS).
Familiarity with data engineering workflows, including ETL, orchestration, and feature pipelines.
Experience with finance datasets and compliance-aware modeling (SOX or similar).

What Sets You Apart

Track record of building scalable, interpretable forecasting models that deliver measurable business impact.
Demonstrated success deploying LLM-based systems with performance monitoring and ethical safeguards.
Experience designing observability frameworks to monitor production models for drift and degradation.
Strong communication and storytelling skills, with the ability to bridge data science and business strategy.
A passion for the future of data science, continuously striving to learn and implement new techniques and technologies

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.

$129,800.00 - $241,200.00

Benefits:

Medical, Dental, and Vision Insurance.
Telehealth coverage
Flexible work schedules and work from home opportunities
Development and career growth opportunities
Open Time Off in addition to 10 paid holidays
401(k) matching program
Adoption Assistance
Fertility treatments

Click here to view a summary overview of our Benefits.

If a Genesys employee referred you, please use the link they sent you to apply.

About Genesys:

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.com.

Reasonable Accommodations:

If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at reasonable.accommodations@genesys.com.

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

_Please note that recruiters will never ask for sensitive personal or financial information during the application phase.