Senior Data Scientist

Sprinklr is seeking a Senior Data Scientist for its Enterprise Business Intelligence team. This role involves leading the full lifecycle of data science and AI solutions, from data model engineering to deploying predictive and recommendation models. The Senior Data Scientist will collaborate cross-functionally, maintain an understanding of business KPIs, and continuously improve model accuracy. They will also create dashboards using PowerBI and mentor team members.

Must Have

• Lead and manage the full lifecycle of data science and AI solutions.
• Develop and deploy predictive models, recommendation models, and other solutions.
• Work closely with engineers, data scientists, analysts, and cross-functional stakeholders.
• Maintain exceptional understanding of business KPIs and related business/customer processes.
• Continuously seek out additional data points to improve model accuracy and applicability.
• Work with leaders, product engineers, and user experience researchers to understand customer data.
• Exhibit excellent communication skills to articulate the model’s impact in business terms.
• Create and maintain dashboards and interfaces using PowerBI.
• Leverage and test multiple methodologies for advanced analysis projects.
• Use analytical rigor and statistical methods to analyze large amounts of data.
• Masters or PhD in a field emphasizing building and maintaining machine learning models.
• 5+ years of work experience in Data Science, building and delivering ML/AI algorithms.
• 5+ years of work experience articulating the value of models and driving business insights.
• Experience with Snowflake, Python, R, SQL.
• Experience in working with Sales, Finance, Marketing, Consumption, and Operational data.
• Experience in building data visualization reports and dashboards for Executives and Stakeholders.
• Strong project and stakeholder management skills.
• Advanced presentation skills.
• Experience with data management, data structures, data ingestion, blending, transformation, and visualization techniques.

Good to Have

• Snowpark experience

Perks & Benefits

• Comprehensive suite of benefits
• Voluntary healthcare coverage in countries where applicable
• Flexible paid time off
• Holidays
• Generous caregiver and parental leaves
• Life and disability insurance
• Health benefits including medical, dental, vision, and prescription drug coverage
• 401k plan with 100% vested company contributions
• Open Mentoring Program

Sprinklr has an exciting opportunity for a Senior Data Scientist to join the Enterprise Business Intelligence team. Sprinklr's BI Team is collaborating closely with other teams across the organization to embrace AI and expand its application throughout the enterprise. The Sr. Data Scientist wilil play an important role in this strategic initiative.

This person will work on all facets of the data model, the semantic model, as well as the tools and interfaces they support. They will engineer the underlying data sources, where needed, to support predictive capabilities, natural language modeling, and AI. They will critically evaluate AI solutions and tools, ensuring that AI use cases are supported through responsible, ethical, trusted and compliant approaches.

The Sr. Data Scientist will design Al/ML algorithms to develop predictions, recommendations, data quality improvements and proactive insights for the organization. They will also serve as a Product Manager of the data science and AI model(s), capturing feedback from stakeholders driving a roadmap for the BI Team.

This role requires ongoing collaboration with front-line managers all the way to executive leadership, across all functional pillars of Sprinklr. Therefore, candidates need exceptional communication skills combined with a deep understanding of the business.

This role will take that insight from business processes and customer relationships to further enhance existing models.

• Lead and manage the full lifecycle of data science and AI solutions, starting with the engineering of the data model to serve as the foundation.
• Develop and deploy predictive models, recommendation models, and other solutions to provide timely insights, recommendations and predictions.
• Work closely with engineers, data scientists and analysts within the BI team, and collaborate cross-functionally with other colleagues and stakeholders throughout the organization.
• Maintain exceptional understanding of business KPIs and related business/customer processes to ensure the relevancy of the model.
• Continuously seek out additional data points that can be leveraged to improve accuracy and applicability of the model’s results.
• Work with leaders, product engineers and user experience researchers to understand customer data and explore opportunities to turn qualitative data into quantitative data for use in recommendation models.
• Exhibit excellent communication skills needed to articulate the model’s impact in business terms, whether to front-line managers or to executive leaders.
• Create and maintain dashboards and interfaces using PowerBI to provide access and interactive capabilities to the model's recommendations and insights.
• Leverage and test multiple methodologies for advanced analysis projects (predictive models, clustering / segmentation, etc.), with the intent to select one that yields the most accurate approach.
• Use analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools, and machine learning techniques and statistics (e. g., predictive models, LTV, propensity models).
• Mentor team members on data and analytical projects, or on cross-functional teams.