Appriss Retail

Manager

• Leverages AI-based tools and platforms to scale outbound outreach and generate qualified meetings with executive personas
• Partners with Director of Growth to co-build account-based outbound strategies targeting high-value accounts and executives with creative, scalable outreach
• Works closely with sales reps to ensure seamless handoff and maximize conversion from meeting to opportunity
• Tracks key metrics, analyzes outreach performance, and iterates quickly to improve meeting conversion rates and pipeline contribution
• Stays current on AI tools, sales technology, and outreach best practices to push modern SDR effectiveness

Relationship Development Manager

Revenue Operations

• Develop and execute the overall Rev Ops strategy in alignment with company revenue goals.
• Partner with executive leadership (CMO, CRO, CFO) on annual planning, goal setting, territory design, and compensation structure to maximize efficiency and attainment.
• Identify and implement key performance indicators (KPIs) and metrics to monitor the health and efficiency of the revenue funnel across all stages.
• Lead initiatives to improve data quality and governance across all revenue systems.
• Design, document, and manage end-to-end operational processes (e.g., lead-to-cash) to ensure consistency, scalability, and adherence to best practices.
• Drive sales productivity by streamlining workflows, automating repetitive tasks, and providing necessary tools and training.
• Oversee sales forecasting and pipeline management methodologies, ensuring accuracy and consistency across the organization.
• Manage the contract lifecycle management (CLM) process in collaboration with legal and finance teams.
• Serve as the primary liaison between Sales, Marketing, Customer Success, Finance, and IT on operational matters.
• Drive cross-functional projects aimed at revenue growth and operational efficiency.
• Own and optimize the RevOps technology stack (e.g., Salesforce CRM, marketing automation, data enrichment tools, business intelligence platforms).

Senior Revenue Operations Manager

Product Manager

• Own product strategy & execution: Define and deliver the roadmap aligned with company objectives, customer outcomes, and measurable ROI.
• Result and Outcome Oriented: Displays a high level of urgency.
• Lead and do: Influence teams and stay hands-on with research, data analysis, and product delivery.
• Customer & data obsessed: Leverage data, user feedback, and behavioral analytics to inform product decisions and validate hypotheses.
• End-to-end ownership: Manage the complete lifecycle — ideation, requirements, prioritization, launch, adoption, and iteration.
• Drive clarity in ambiguity: Make smart, timely decisions even with imperfect information; balance speed with strategic rigor.
• SaaS and platform mindset: Design and scale multi-tenant SaaS capabilities with a focus on reliability, configurability, and ease of integration.
• Technical fluency: Understand APIs, data pipelines, and how AI/ML-driven solutions are built, integrated, and deployed to customers.
• Retail domain understanding: Translate complex retail returns, claims, and post-purchase workflows into simple, high-impact digital experiences.
• Cross-functional collaboration: Partner closely with engineering, data science, design, and GTM to drive alignment and deliver on roadmap priorities.
• Client-facing leadership: Present product vision, prototypes, and outcomes to enterprise clients and internal executives with credibility and confidence.

Director of Product Management

Marketing

• Owns the strategy and flawless execution of industry events, owned events, and executive dinners
• Partners with the Director of Growth and Sales teams on outreach strategy
• Designs unique, memorable, and detail-oriented activations
• Works in conjunction with the Director of Growth to track field marketing impact on pipeline and revenue
• Manages budgets, timelines, and vendors with precision
• Embraces AI and LLM best practices to enhance event strategy

Senior Field Marketing Manager

Data Scientist

• Write, maintain, and optimize production-level Python and SQL code for data pipelines, MLOps workflows, and related systems.
• Analyze structured and unstructured datasets to identify trends, patterns, and opportunities for improvement.
• Design, implement, and maintain automated data ingestion, transformation, and validation pipelines.
• Contribute to the design, testing, and deployment of predictive and prescriptive models.
• Support deployment of pipelines and ML models, including standing up and managing relevant cloud infrastructure.
• Collaborate with engineering, product, and business teams to translate requirements into scalable, code-driven solutions.
• Apply rigorous statistical and software engineering best practices to ensure accuracy, reproducibility, and reliability.
• Continuously evaluate and integrate tools, frameworks, and methods that improve efficiency, scalability, and maintainability.
• Communicate results and recommendations clearly to both technical and non-technical audiences.
• Adhere to data governance, security, and privacy standards.

We’re seeking a Senior Data Scientist and natural storyteller to work within the Data Science team, serving as a critical link between technical analytics output and client-facing communication.
Analyze consumer data and machine learning model decisions to uncover patterns, trends, and anomalies relevant to client business outcomes.
Work with large datasets using SQL to extract, clean, and analyze data to support custom analyses.
Build automated analyses using Python and SQL that can be shared internally and feed production reporting endpoints.
Partner with the Revenue Organization to create and deliver PowerPoint presentations that effectively communicate insights to non-technical stakeholders.
Collaborate with other members of the Data Science team to ensure analysis is technically accurate and aligned with business needs.
Translate complex machine learning concepts into understandable business narratives and visualizations.
Leverage software development best practices when working with data pipelines, code repositories, and version control.