Sales Operations _ Marketing

Responsibilities CRM Data Management Audit CRM records (Zoho / HubSpot / Salesforce) for accuracy, completeness, and duplication. Enrich contact and company records using AI research tools. Identify, merge, or remove duplicate records; keep duplicate rate below 2%. Maintain CRM data completeness above 95%. Data Modeling & Segmentation Build segmentation models for target accounts by industry, geography, and size. Build and maintain the lead scoring model; update it quarterly. Apply data criteria for Tier 1 / Tier 2 / Tier 3 account classification, based on inputs from the Research Analyst. Automation & AI Workflows Automate repetitive data collection and data-entry tasks using Python and AI tools (ChatGPT, Perplexity, Claude, NotebookLM). Build or maintain integrations that pull data from LinkedIn Sales Navigator, company websites, and public registries into the CRM. Ship at least 2 automation improvements per quarter that measurably cut manual research or data-entry time. Dashboards & Reporting Build and maintain Power BI or Tableau dashboards for CRM data quality, pipeline coverage, and market coverage. Automate recurring data feeds for the monthly competitor intelligence report and quarterly market opportunity report. Prepare the underlying numbers, charts, and tables for industry reports and executive briefing notes (research and narrative stay with the Research Analyst/Manager). Database & Infrastructure Maintain master prospect and account databases across Australia, UK, USA, and new verticals as they're added (e.g., NDIS). Structure data schemas used for account-based research and event target lists. Keep data consistent across CRM, spreadsheets, and BI tools — no conflicting numbers across systems. Cross-functional Support Convert raw research output from the Research Analyst into structured, usable datasets. Work with internal automation/IT teams to scale tools built for research and CRM workflows. Pull and score event attendee data (target lists, tier classification) ahead of each event. Qualifications and Experience 2–5 years in data analysis, CRM operations, marketing/sales analytics, or business intelligence. Experience handling B2B data across multiple geographies preferred (Australia, UK, USA). Works comfortably with messy, unstructured data and turns it into clean, usable datasets. High attention to detail — low tolerance for data errors. Can prioritize independently across requests from Sales, Marketing, and Leadership without constant direction. Picks up new AI/automation tools on their own, without being asked. Experience in a fast-scaling services or outsourcing company is a plus, not a requirement. Key Skills Required Python (data manipulation, scripting, automation) SQL Advanced Excel / Google Sheets (pivot tables, XLOOKUP, macros) Power BI or Tableau (at least one) CRM platform experience: Zoho, HubSpot, or Salesforce (at least one) AI research/automation tools: ChatGPT, Perplexity, Claude, NotebookLM Data cleaning and deduplication Preferred API integration basics Web scraping (e.g., BeautifulSoup, Selenium, or similar) Lead scoring / segmentation methodology