Smartsheet is establishing a new Enterprise Insights & Intelligence team to centralize ownership of corporate metrics, analytics governance, and self-serve data enablement. This is a foundational hire — you will help build this function from the ground up, with direct visibility to senior leadership and the opportunity to shape how the entire organisation consumes and trusts its data.

We are looking for a Senior Business Intelligence Engineer who can operate across three strategic pillars: automating and governing corporate executive reporting, standardising metrics and reporting practices at scale, and enabling self-serve and AI-powered data solutions. Day to day, this means you could be building an automated executive scorecard, codifying metric definitions into a governed semantic layer, standing up an AI agent that lets business users query trusted data in natural language, or leading enablement sessions on our analytics platforms. The thread connecting all of it is ensuring that Smartsheet's data is trusted, consistent, accessible, and ready for both human and AI consumption.

This is not a traditional reporting or data science role. You will work across dbt, MetricFlow, Snowflake, and Databricks to build the governed data layer that underpins everything — from board-level scorecards to LLM-powered insights to self-serve dashboards.

You Will

• Design, build, and maintain governed metric models — standardised, reusable definitions of business KPIs that dashboards, reports, and AI agents all query from a single source of truth
• Own the automation and maintenance of corporate scorecards and executive reporting (SLT/XLT), ensuring trusted, timely data with AI-powered anomaly detection and alerting
• Conduct deep dives on key KPIs and company goals, surfacing actionable insights and translating short- and long-term business priorities into data-driven recommendations shared via reviews and async updates
• Lead metric certification and governance — maintain a centralised KPI glossary, standardise dashboards, and retire stale reporting assets
• Build AI agent integrations (MCP servers, skills, subagents) that allow tools like Claude and Snowflake Cortex to query enterprise data through the semantic layer with metric-correct SQL
• Drive self-serve analytics enablement — documentation, training, dashboard quality checks, and experimentation governance across Amplitude, Tableau, and other platforms
• Partner with Product, Engineering, Finance, GTM, and Customer Success to align metric definitions and data sources cross-functionally
• Translate qualitative UX signals and customer feedback into measurable data pipelines

You Have

• Bachelor's degree (B.Tech / B.E. / B.Sc.) in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
• 5+ years of experience in analytics engineering, BI engineering, data engineering, or a closely related role
• Experience with KPI design and insight generation — ability to define meaningful metrics, analyse trends, identify anomalies, and communicate findings that drive business decisions
• Familiarity with dbt (dbt Core or dbt Cloud) and concepts like YAML-based metric definitions and reusable data models; hands-on experience is a plus but not required
• Deep SQL expertise with experience working in cloud data platforms such as Snowflake and/or Databricks
• Experience building semantic layers, governed data models, or canonical metric definitions for downstream consumption
• Working familiarity with AI/LLM tooling — concepts such as MCP (Model Context Protocol), agentic frameworks, or tool-use patterns for large language models
• Proficiency with one or more BI/visualisation tools (Tableau, Amplitude, or similar)
• Strong cross-functional collaboration skills and excellent async communication across time zones (IST / US Pacific overlap expected)
• A proactive, ownership-driven mindset — comfortable building new processes and standards in a greenfield environment

Preferred Qualifications

• Experience building AI agent skills, subagents, or MCP server integrations for LLMs
• Hands-on experience using agentic coding platforms (Claude Code, Cursor, Windsurf, etc.) to streamline and automate analytics workflows
• Software engineering experience (Python, JavaScript/TypeScript) with the ability to contribute to application-level instrumentation code
• Experience with event taxonomy design, behavioural analytics pipelines, or product instrumentation (Amplitude, Segment, etc.)
• Familiarity with metric governance frameworks, data catalogues, or data quality tooling
• Prior experience working in a SaaS or enterprise software environment

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Manager AI/ML Ops Engineering, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Focus on team members and coaching them to play to their strengths, grow and deliver peak performance
• Lead and mentor a team of AI/ML Ops engineers and operations specialists.
• Define and govern solutions for AI/ML operations, ensuring scalability, cost-efficiency, and reliability
• Develop and maintain standardized AI/MLOps workflows, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines
• Delegate and harness the aggregate strength of your team.
• Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values.
• Actively helps individuals and the overall team to set priorities and focus on delivery of commitments
• Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security
• Lead and facilitate cross-team interactions, communication, and dependencies
• Ensure all changes are fully tested before being deployed
• Ensure deployment plans are well-considered and include appropriate scalability and load tests
• Work with stakeholders to align AI projects with business strategies.
• Ensure all AI/ML Ops solutions adhere to regulatory compliance, security, and ethical guidelines
• Drive Engineering and Operational excellence initiatives
• Perform other duties as assigned
  
  

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Experience building teams through recruiting and retention
• Experience in Leading and Mentoring a team of ML engineers and operations specialists.
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI & Data Governance Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Develop and enforce AI&Data governance frameworks, including bias detection, explainability, and model lifecycle management
• Ensure adherence to data privacy laws and security regulations, managing risks in AI and data pipelines
• Implement data lineage, metadata, data management, and quality frameworks
• Implementing tools to track data from its source to the final AI output. If a model breaks, you need to know exactly which data point caused the drift
• Define roles for data custodians, users, and AI developers, promoting transparency and fairness.
• Partner with Legal, Data Engineering, and Security teams to embed security and privacy into AI workflows and data products
• Implement governance tools (e.g., Collibra, Informatica) and automate audit procedure
• Oversee data stewardship to ensure data accuracy, integrity, and privacy throughout its lifecycle
• Designing and enforcing the rules for how data is collected, stored, and used—specifically focusing on data privacy (GDPR, CCPA) and AI regulations (like the EU AI Act).
• AI Ethics & Bias Mitigation: Establishing "Responsible AI" standards. This involves auditing models for algorithmic bias, ensuring transparency (Explainable AI), and managing the ethical implications of automated decision-making
• Risk Management through Identification of Shadow AI (unauthorized use of AI tools) and managing the risks associated with third-party LLM providers
  
  

You Have:

• Experience in AI Governance across foundational pillars like AI Organization, Legal, Regulatory Compliance, Ethics, Transparency, Interoperability, Data/AIOps Infrastructure, AI protection and Security
• AI Risk Assessment & Management, Auditability & Transparency, AI Policy Development
• Databricks AI Governance Framework (DAGF), Databricks Security Framework (DASF), MLFlow, Unity Catalog, RAG Governance
• Programming languages like Python and SQL
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• In-depth understanding of AI, GenAI, LLMs, data quality assessment, and metadata management.
• Regulatory Knowledge in GDPR, EU AI Act, and industry-specific regulations (e.g., HIPAA, Financial Services)
• Lineage Tracking with automatic capture of end-to-end data flow (from ETL to BI/AI) to understand dependencies.
• Auditability with centralized logs to allow compliance teams to monitor access and usage of data and AI models
• Knowledge of tools for Model Auditing towards Bias detection,, monitoring, and mitigating bias
• Understanding of data masking, encryption, and SOC2
• Certifications like CIPP (Privacy), CDMP (Data Management), or specialized AI ethics certifications is preferable
• Enterprise SaaS software solutions with high availability and scalability
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective.

You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. 

You Will:

Model and Pipeline Automation 

• Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. 
• Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
• Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.

Governance & Compliance

• Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.

Performance Monitoring

• Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. 
• Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.

Cross-Functional Collaboration

• Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
• Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.

Architecture and Infrastructure Management

• Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
• Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
• Distill complex ML concepts into easy-to-follow technical documentation.

You Have:

• 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 
• 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
• 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
• Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. 
• Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
• Experience developing, documenting, and supporting REST APIs
• A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. 

A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. 
• Contribute to the design standards and architectural principle standards, designs and processes.
• Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV).
• Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines.
• Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight.
• Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster.
• Create and implement data testing plans, encompassing data validation, data quality assessment, and regression testing, to identify anomalies, inconsistencies, or errors in produced datasets.
• Mentor and guide teams and help drive high standards across the team by conducting design reviews and engineering ideation forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 6+ years of experience in advanced data modeling using Data Vault (DV 2.0), dbt, and Snowflake.
• Proven experience in building analytics systems with data transformation, dependency, and workload management (Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab, SQL).
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Familiarity with data governance principles for maintaining datasets to enable a single source of truth.
• Familiarity with self-serve product analytics tools (Amplitude, Thoughtspot, Tableau, Gainsight, etc.).
• Knowledge of code management and CI/CD practices (GitLab, Airflow, Snowflake, Terraform).
• Familiarity with AWS solutions such as S3, EC2, VPC.

As a global leader in Collaborative Work Management and with a market cap of $10bn we’ve experienced incredible growth in EMEA, expanding from 1 team and 3 engineers in 2018 to 9 teams with over 70 engineers in 2024. As we expand into India and build out a new operation, we're searching for a talented and motivated Principal Analytics Engineer (Data Architect) to serve as a thought leader in our data-driven decision-making. You will be responsible for the end-to-end system design and architecture of our business critical analytical systems (DWs). This role will be responsible for the design and development of a governed, reliable, and scalable analytics ecosystem, transforming raw data into high-value, performant data products for DS/ML, analytics, and reporting.

A key aspect of this role is providing thought leadership and architecting efficient, large-scale data transformation systems within Snowflake. You will have demonstrated experience architecting data solutions for SaaS companies, specifically within the Go-To-Market (GTM), Marketing, Customer Experience, and Financial business domains. Working as a strategic advisor to BI analysts, Data Scientists, and business leadership, you will drive the organization's data strategy, ensure data accessibility, and foster data democratization across the enterprise.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Lead the end-to-end system design and architecture for large, complex analytics systems, optimizing data transformations from our data lake in Snowflake into analytical data products (DWs).
• Define and drive the adoption of design standards, architectural principles, and data modeling methodologies (including Data Vault (DV 2.0) and dimensional modeling) across the organization.
• Propose and drive strategic initiatives and coordinate the technical roadmap for analytical systems across the engineering organization partnering closely with the Big Data Platforms (BDP) team.
• Serve as the data architect for critical SaaS business domains, including Go-To-Market, Marketing, Customer Experience, and Finance, translating ambiguous business problems into scalable technical analytical solutions.
• Develop and implement the organization's data strategy for data quality, observability, and testing, raising the bar for engineering quality.
• Architect and guide teams to build and maintain a governed, robust, reliable, and scalable analytics system leveraging Gen AI capabilities including AI-assisted code development practices.
• Act as a trusted advisor to BI analysts, data scientists, and business leaders, educating and advising leadership on technical data topics and data accessibility strategies.
• Foster data democratization via activation of data on critical platforms like Smartsheet Platform, Amplitude, ThoughtSpot, Gainsight & Salesforce.
• Actively mentor analytics engineers and provide mentorship across disciplines, leading forums such as guilds, design reviews, and engineering forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 12+ years of experience in advanced data modeling, data architecture, and data warehousing. This role is expected to do development activities in combination of the data architecture scope, so hands-on experience is necessary.
• Deep expertise and 10+ years of hands-on experience with Data Vault (DV 2.0) and Dimensional Modeling.
• Expert-level knowledge of modern data stacks, including Snowflake, dbt, and data orchestration tools (e.g., Airflow, GitLab pipelines).
• Proven experience architecting and building analytical products for SaaS companies in GTM, Marketing, Customer Experience, and Financial data domains.
• Comprehensive understanding of data topologies (e.g., data mesh, hub/spoke) and data modeling methodologies (e.g., Data Vault, Kimball, Inmon).
• Demonstrated ability to drive clarity in ambiguous environments where the strategy may not be defined.
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Exceptional communication skills, with experience educating and advising senior leadership and mentoring teams across disciplines.
• Strong knowledge of data governance principles, CI/CD practices (e.g., GitLab), self-serve analytics tools (e.g., Amplitude, ThoughtSpot), and cloud architectures (AWS preferred).

Smartsheet is seeking a Senior Data Scientist to drive growth and customer retention through Applied AI and advanced analytics. With thousands of subscribing organizations and millions of users, you will have the opportunity to make a meaningful impact by leveraging data science to drive Sales, Customer Success, and Monetization strategies. You are curious, have strong data science and machine learning skills and the ability to communicate key insights effectively. You will work primarily with Go to Market Teams and will be a part of Smartsheet's Data Science & Business Intelligence team.

You Will:

• Partner with Sales and Customer Success teams, understand their goals, and execute on opportunities to draw relevant insights and drive tangible impact
• Develop and implement machine learning based Cross-sell/Upsell models and Product Recommender models to drive Sales & Monetization
• Build and deploy predictive models for Customer Churn and identify proactive churn risk prediction signals to drive retention
• Drive the full analytics lifecycle from understanding the business objective, analyzing the data to developing automated reporting and visualizations
• Collaborate with cross-functional teams to integrate data science solutions into business processes
• Effectively present analysis to both technical and non-technical audiences and give data-based recommendations to encourage data-driven decisions 
• Drive a data culture within the Go To Market  teams

You Have:

• Bachelor's degree and 8+ years of experience (or 10+ years of experience)
• Extensive knowledge and practical experience in several of the following areas: Applied AI, machine learning, statistics, propensity modeling, churn prediction and recommender systems
• Proficient analytical skills for problem solving; can perform descriptive analysis, diagnostic analysis, predictive analysis and prescriptive analysis.
• Strong programming skills in Python or R
• Proficient in SQL and skilled in visualization tools (ex. Tableau)
• Strong track record of forming effective cross-functional partnerships
• Experience using data to meaningfully impact Sales & Customer Success strategy execution
• Experience communicating analysis clearly to others
• Ability to research and learn new technologies, tools, and methodologies
• Ability to thrive in a dynamic environment, find opportunities and execute in both independent and collaborative environments
• As a senior member of the data science team help mentor and help grow members of the team