Genesys Cloud Services, Inc.
Finance Data Scientist
Genesys Cloud Services, Inc., Menlo Park, California, United States, 94029
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.
Summary of Position:
We are seeking a highly skilled Data Scientist to drive data-driven decision-making across the organization by applying advanced machine learning and statistical techniques. This role is pivotal in solving complex business challenges, driving company strategy, and mentoring team members on advanced data science practices. You will work at the intersection of data science, finance, and business operations, building models that uncover hidden insights in customer behavior, help to optimize revenue streams, improve customer experience, and enhance operational efficiency.
A core focus of the role will be productionizing and deploying scalable models across different business functions, ensuring seamless integration into workflows. The ideal candidate will possess strong expertise in model interpretation, performance evaluation, and stakeholder communication, making machine learning outcomes understandable and actionable for non-technical audiences. This position will require collaboration with cross-functional teams to ensure the models continuously adapt to business needs and deliver measurable results.
You'll play a hands-on role in all stages of the data science lifecycle-from data preparation, feature engineering, and model development to deployment, monitoring, and iterative improvement. A passion for ideation, problem-solving, and leveraging emerging technologies (e.g., GPTs, LLMs) will set you apart.
Location:
US Remote (not limited to the states that the job is tagged to) Key Responsibilities: Model Development, Interpretation, and Evaluation
Collaborate with data scientists and engineers to develop classification and regression models, ensuring predictions are accurate, explainable, and actionable for stakeholders. Apply interpretability techniques to make model behavior transparent and build trust with non-technical teams. Assess and monitor model performance using a range of metrics (e.g., accuracy, F1-score, AUC-ROC, mean squared error, R) and identify areas for improvement. Experience with decision trees, ensemble methods, and LSTM models is a plus.
Feature Engineering and Data Exploration
Develop, refine, and test new features to improve model performance and predictive accuracy. Prepare, clean, and transform datasets, ensuring high data quality and consistency for model input.
Productionization and Model Deployment
Deploy machine learning models into production environments, ensuring they are scalable, efficient, and maintainable. Collaborate with internal teams to integrate models into business processes and automate workflows. Monitor deployed models for drift, accuracy degradation, and performance bottlenecks, and apply retraining strategies as needed. Utilize CI/CD pipelines and MLOps best practices to streamline deployment and maintenance.
Data Visualization and Storytelling
Create interactive dashboards and visualizations to communicate insights effectively. Translate complex machine learning outputs into compelling narratives that align with business goals and engage non-technical stakeholders.
Insight Generation and Business Impact
Detect trends, anomalies, and patterns to uncover actionable insights that guide strategic business decisions. Measure the impact of data science initiatives on key business outcomes and continuously improve models to align with evolving objectives.
Stakeholder Collaboration and Communication
Partner with finance, business, product, sales, and operational teams to drive value across the company. Communicate model strengths, limitations, and predictions effectively to both technical and non-technical audiences. Act as a trusted advisor to stakeholders, ensuring alignment between data science solutions and business needs.
Key Qualifications: At least 3 years of experience as a Data Scientist 3-5 years of SaaS experience . A focus on supporting product or sales is a plus. Proficiency in Python or R for data manipulation and analysis Strong proficiency in data visualization tools Proven expertise in explaining and interpreting machine learning model predictions for stakeholders Deep experience with model performance evaluation Experience with building and deploying complex machine learning models in production Demonstrated success in delivering actionable insights/KPIs to executives (customer-related insights preferred) Proficiency in SQL and Excel for large data set analysis Excellent storytelling and communication skills, both written and verbal Naturally empathetic, trustworthy, collaborative, and curious Ability to thrive in ambiguous, fast-paced environments and influence cross-functional teams Nice to have:
Experience with large language models (LLMs), building GPTs, and leveraging generative AI tools 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 More details about our company benefits can be found at the following link:
https://mygenesysbenefits.com If a Genesys employee referred you, please use the link they sent you to apply. About Genesys: Genesys empowers more than 8,000 organizations in over 100 countries 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, Genesys delivers the future of CX to organizations of all sizes so they can provide empathetic, personalized experience at scale. As the trusted platform that is born in the cloud, Genesys Cloud helps organizations accelerate growth by enabling them to differentiate with the right customer experience at the right time, while driving stronger workforce engagement, efficiency and operational improvements. Reasonable Accommodations: If you require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you or someone you know may reach out to HR@genesys.com. You can expect a response from someone within 24-48 hours. Genesys is an equal opportunity employer committed to equity 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.
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US Remote (not limited to the states that the job is tagged to) Key Responsibilities: Model Development, Interpretation, and Evaluation
Collaborate with data scientists and engineers to develop classification and regression models, ensuring predictions are accurate, explainable, and actionable for stakeholders. Apply interpretability techniques to make model behavior transparent and build trust with non-technical teams. Assess and monitor model performance using a range of metrics (e.g., accuracy, F1-score, AUC-ROC, mean squared error, R) and identify areas for improvement. Experience with decision trees, ensemble methods, and LSTM models is a plus.
Feature Engineering and Data Exploration
Develop, refine, and test new features to improve model performance and predictive accuracy. Prepare, clean, and transform datasets, ensuring high data quality and consistency for model input.
Productionization and Model Deployment
Deploy machine learning models into production environments, ensuring they are scalable, efficient, and maintainable. Collaborate with internal teams to integrate models into business processes and automate workflows. Monitor deployed models for drift, accuracy degradation, and performance bottlenecks, and apply retraining strategies as needed. Utilize CI/CD pipelines and MLOps best practices to streamline deployment and maintenance.
Data Visualization and Storytelling
Create interactive dashboards and visualizations to communicate insights effectively. Translate complex machine learning outputs into compelling narratives that align with business goals and engage non-technical stakeholders.
Insight Generation and Business Impact
Detect trends, anomalies, and patterns to uncover actionable insights that guide strategic business decisions. Measure the impact of data science initiatives on key business outcomes and continuously improve models to align with evolving objectives.
Stakeholder Collaboration and Communication
Partner with finance, business, product, sales, and operational teams to drive value across the company. Communicate model strengths, limitations, and predictions effectively to both technical and non-technical audiences. Act as a trusted advisor to stakeholders, ensuring alignment between data science solutions and business needs.
Key Qualifications: At least 3 years of experience as a Data Scientist 3-5 years of SaaS experience . A focus on supporting product or sales is a plus. Proficiency in Python or R for data manipulation and analysis Strong proficiency in data visualization tools Proven expertise in explaining and interpreting machine learning model predictions for stakeholders Deep experience with model performance evaluation Experience with building and deploying complex machine learning models in production Demonstrated success in delivering actionable insights/KPIs to executives (customer-related insights preferred) Proficiency in SQL and Excel for large data set analysis Excellent storytelling and communication skills, both written and verbal Naturally empathetic, trustworthy, collaborative, and curious Ability to thrive in ambiguous, fast-paced environments and influence cross-functional teams Nice to have:
Experience with large language models (LLMs), building GPTs, and leveraging generative AI tools 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 More details about our company benefits can be found at the following link:
https://mygenesysbenefits.com If a Genesys employee referred you, please use the link they sent you to apply. About Genesys: Genesys empowers more than 8,000 organizations in over 100 countries 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, Genesys delivers the future of CX to organizations of all sizes so they can provide empathetic, personalized experience at scale. As the trusted platform that is born in the cloud, Genesys Cloud helps organizations accelerate growth by enabling them to differentiate with the right customer experience at the right time, while driving stronger workforce engagement, efficiency and operational improvements. Reasonable Accommodations: If you require a reasonable accommodation to complete any part of the application process or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you or someone you know may reach out to HR@genesys.com. You can expect a response from someone within 24-48 hours. Genesys is an equal opportunity employer committed to equity 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.
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