Job Title: Reporting / Data Analyst Location: Remote - LATAM Schedule: Monday - Friday. 9AM - 5PM CST USD Salary range: (Monthly USD) $1,500 – $3,000 (Negotiable based on expertise) We are seeking a Reporting / Data Analyst to own dashboard management, performance tracking, and insight generation across marketing channels. This role is focused on maintaining reporting consistency, analyzing performance data, and surfacing actionable insights to the activation team. The ideal candidate is highly analytical, detail-oriented, and experienced in working across GA4, ad platforms, and tracking systems. Responsibilities Dashboard Management - Build, maintain, and update reporting dashboards - Ensure data accuracy and consistency across reports - Standardize reporting frameworks - Troubleshoot data discrepancies Performance Analysis & Insights - Analyze marketing performance across channels - Identify trends, opportunities, and issues - Translate data into actionable insights - Support decision-making with clear reporting Platform & Tracking Management - Work within GA4, ad platforms, and call tracking tools - Ensure proper tracking and attribution - Validate data integrity across sources - Support tagging and tracking implementation Reporting Consistency & Support - Maintain standardized reporting processes - Support internal and client-facing reporting needs - Collaborate with activation teams - Ensure timely delivery of reports

Job DetailsLevel: EntryJob Location: US Remote - Hackensack, NJ 07601Position Type: Full TimeEducation Level: Bachelors DegreeSalary Range: $80,000.00 - $95,000.00 SalaryTravel Percentage: 0-10 %Job Shift: DayJob Category: Information TechnologyPosition Title: Associate Data Analyst - Bioinformatics Operations Classification: Exempt Reports to: Sr. Director of Data Engineering & Bioinformatics Primary Objective: The Associate Data Analyst - Bioinformatics Operations supports day-to-day data operations across Champion Oncology's bioinformatics and data engineering workflows. DUTIES, RESPONSIBILITIES AND PRODUCTIVITY EXPECTATIONS: Organize, track, and maintain structured biological and analytical datasets across shared storage and cloud environments. Execute and monitor secure data transfers between internal systems, cloud platforms (e.g., AWS), collaborators, and clients, validating data integrity and completeness. Run standardized bioinformatics pipelines (e.g., WES, RNA‑seq, proteomics) using established workflows and frameworks such as Nextflow. Monitor pipeline execution, review logs, identify common failure modes, and escalate issues as needed. Perform defined quality control checks on pipeline outputs and compile run summaries, QC metrics, and delivery checklists. Prepare organized output packages for downstream analysis or client delivery. Collaborate with bioinformaticians, DevOps engineers, and other Data Team members and contribute to documentation, runbooks, and SOPs supporting data and pipeline operations. QualificationsKNOWLEDGE, SKILLS, AND ABILITIES: Working familiarity with Linux command‑line environments. Experience with basic scripting (Python and/or Bash). Foundational understanding of analytical or biological data types, or strong demonstrated interest in bioinformatics workflows. Strong organizational skills and attention to detail when working with large datasets. Ability to follow established procedures while exercising judgment on when to escalate issues. Effective written and verbal communication skills in a collaborative, remote‑first environment. EDUCATION AND EXPERIENCE: Bachelor’s degree in Data Science, Bioinformatics, Computational Biology, Computer Science, or a related field, or equivalent practical experience. Exposure to NGS or other omics data types (e.g., FASTQ, BAM, VCF) preferred. Experience running or supporting workflows using Nextflow or similar pipeline frameworks preferred. Introductory experience with cloud platforms (AWS preferred) is a plus. PHYSICAL DEMANDS AND WORK ENVIRONMENT: Must be able to sit for long periods of time using a computer in a typical office environment in a multi-level facility or home office. This description reflects management’s assignment of essential functions, it does not proscribe or restrict the tasks that may be assigned. We celebrate diversity and are committed to creating an inclusive environment for all employees.

• Live by and champion all of our core values (#ownership, #empathy, #day-one, and #humility). • Build and maintain durable, documented, tested models in dbt that power GTM reporting (e.g., pipeline, funnel, conversion, bookings, forecasting, rep performance, account health). • Design dimensional models (facts/dimensions), metrics definitions, and “one version of the truth” datasets to make analysis repeatable and trustworthy. • Develop and maintain Looker explores, dashboards, and standardized reporting that enable self-serve by the GTM organization. • Implement data quality checks, monitoring, and model documentation so stakeholders can confidently act on results. • Partner with data engineering on upstream improvements (instrumentation, source system hygiene, pipeline reliability). • Collaborate with GTM stakeholders to clarify business questions and translate them into analysis plans, metrics, and decision frameworks. • Perform analysis using SQL (and Python as needed) to identify trends, diagnose performance, and recommend actions (e.g., funnel bottlenecks, win-rate drivers, deal velocity, territory/segment opportunities). • Build GTM narratives that connect data to decisions—clearly communicating insights with business context to leaders and cross-functional partners. • Proactively monitor performance and adoption signals to surface risks, anomalies, and opportunities—then drive stakeholders toward resolution. • Identify high-leverage GTM “insight bottlenecks” and design data products to solve them (e.g., standardized KPI hubs, automated pipeline risk alerts, self-serve funnels, guided explorations, executive views). • Leverage LLMs/AI to accelerate insight workflows—examples might include: AI-assisted “metric explainers” embedded into dashboards, natural-language Q&A experiences over curated GTM datasets, automated insight summaries / anomaly narratives for weekly GTM reviews, guided self-serve templates (“answer this question in 3 clicks”) for common GTM use cases. • Establish success metrics for data products (e.g., reduced time-to-insight, increased self-serve usage, fewer ad-hoc requests, improved forecast accuracy). • Work independently in ambiguous environments—framing problems, generating hypotheses, and leading toward outcomes. • Manage multiple priorities and communicate clearly through Slack, docs, and live stakeholder readouts. • Contribute to team standards (modeling patterns, documentation, code review, stakeholder intake). • Mentor other analysts through collaboration, query/design feedback, and best practices (where applicable to your team structure).

• Partner with key stakeholders within the Workforce Management team and cross-functionally within HR, Finance, Store/Retail Operations and IT on KPI and data delivery/visualization needs • Participate in various workstreams to provide a foundation in advanced application of data intelligence, processes and tools • Extract relevant data from source databases to outline key trends around demand planning, staffing, and scheduling • Utilize data visualization to bring data to life and tell a compelling story built around actionable insights and support the communication of solutions to stakeholders • Evolve the data analytics and reporting function by automating many of the time intensive (but largely static) data pulls and dashboards/visualizations being performed today, while incorporating new ideas and initiatives • Build and maintain self-service reporting and scenario planning tools to place the intelligence of HR workforce planning in store operations’ hands