Vetted Customer Segmentation Professionals

Amit swami

Screened ReferencesModerate rec.

Senior Performance Marketing Manager specializing in paid media and e-commerce growth

Jaipur, India7y exp

“Performance marketer with hands-on experience managing a $50K+/month account across Meta Ads and Google Ads. They describe a practical testing and optimization approach using multiple ad sets, creative variations, event tracking, and UTM analysis, and report achieving a 4x ROAS while troubleshooting issues across the full funnel.”

“Analytics-focused candidate with hands-on project experience in SQL data preparation and Python-based churn modeling. They demonstrated a practical approach to turning messy multi-source data into reporting tables, validating data quality rigorously, and translating churn insights into targeted retention strategies.”

“Lifecycle/digital marketer with experience leading a new product launch using multi-touch email drip campaigns and digital ads to drive both website engagement and in-store foot traffic, reporting improved ROI. Uses past-buyer and survey-driven segmentation plus A/B testing (creative/copy) and web engagement metrics to optimize performance, and has supported cross-functional event marketing with merchandising and sales enablement materials.”

Diana Bacero

Screened

Executive Customer Success & Operations leader specializing in B2B SaaS (CPM/FP&A)

Arcadia, CA18y exp

“Customer lifecycle/CRM practitioner with experience at DripJobs and Solver, focused on onboarding, retention, and customer education. Drove a 51% churn reduction in 90 days by overhauling onboarding with pre-training automation (Close CRM) and CS playbooks, and boosted training sign-ups 37% by shifting existing-customer marketing into CS using Totango and industry-tailored messaging.”

“Analytics professional with experience across Dreamline AI, Ultron Technologies, and Infolabz, building SQL/Python data pipelines and BI dashboards for incentive, FMCG, and retail use cases. Stands out for turning messy multi-source data into trusted reporting, automating recurring analytics, and tying dashboard adoption to measurable business outcomes like 50% faster reporting and 30% ROI improvement.”

“Data-driven growth and partnerships professional with experience leading an analytics/reporting vendor rollout end-to-end (vendor selection via stakeholder interviews and PoC, then negotiating scope/pricing/support and tracking adoption/efficiency/accuracy KPIs). At PC Financial, built regression and segmentation models to optimize multi-channel targeting (in-app/email/push), driving +15% campaign engagement and +10% PC Optimum offer loads, and ran behavior-triggered lifecycle experiments that lifted upsell conversion by 20%.”

“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”

“Performance marketer focused on scaling DTC ecommerce, with hands-on ownership of a ~$200K/month Meta/Google/TikTok program for a low-8-figure fashion brand. Took the account in-house from a long-tenured agency, rebuilt the structure and creative testing system, and reached a 3.5 ROAS target within two months while driving record Q4 results. Prefers contract/project-based work but is open to full-time for $165K+ with high-growth scaling challenges.”

Sree Manasa Vuppu

Screened

Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG

Charlotte, NC5y exp

“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”

Ttanvi Tummapudi

Screened

Junior Data Scientist specializing in machine learning, predictive modeling, and applied AI research

2y exp

“Data scientist/researcher who has built two multimodal LLM systems: an AI-assisted medical triage pipeline using GPT-4o vision + RAG with confidence-scored red/yellow/green outputs, and a master’s project on multimodal cyberthreat detection combining multiple models and using TinyLlama to generate human-readable risk reports. Also partnered with business analysts at Sanvar Technologies to deliver a churn prediction pipeline and Tableau dashboard for decision-making.”

“Sales professional at AutoSherpa who partners closely with product/engineering to resolve CRM data-sync issues affecting pipeline accuracy and sensitive customer data handling. Experienced running multiple customer onboardings in parallel using structured tracking (CRM/project boards), early risk logging, and weekly stakeholder syncs; targeting $100k base and open to equity.”

Ritika Sisodiya

Screened

Junior Data Scientist specializing in statistical modeling and machine learning

California, USA2y exp

“AI Researcher with production experience building a real-time computer-vision detection pipeline augmented by an LLM-based verification layer to cut false positives (~78%) and reach ~90% real-world accuracy. Also partners cross-functionally with Product/Sales/Marketing to shape AI feature prioritization and market positioning using analysis and interactive dashboards.”

“Marketing and product-focused analytics candidate with hands-on experience turning messy large-scale data from Hadoop/HDFS, Azure Data Lake, and transaction systems into validated reporting tables. They combine SQL and Python automation with strong metric design, cohort/retention analysis, and stakeholder-friendly dashboards, including a reported 30% query performance improvement and weekly reporting automation.”

“Built an end-to-end agentic population health strategy copilot for healthcare leadership, turning broad chronic disease questions into structured, evidence-backed strategy briefs. Stands out for combining healthcare domain knowledge with production-grade GenAI implementation, including LangGraph orchestration, Databricks/MLflow deployment, human review, and quality gates focused on citations, metrics, risks, and safety.”