Data Analyst - Guidance
Job description
About the role
You will join a specialized research and development unit dedicated to refining virtual fencing technology for livestock management. This position blends deep analytical work with hands-on domain immersion, requiring you to become an authority on how animals interact with the guidance system. You will collaborate closely with a fellow analyst to own the guidance data domain, delivering insights that directly influence product evolution. The role demands a hybrid presence, splitting time between the Auckland headquarters and the research farm in Morrinsville to observe animal behavior firsthand. It is designed for a professional eager to transcend traditional analysis boundaries by engaging in data engineering and backend-adjacent technical challenges. You will translate complex behavioral datasets into clear narratives that steer the strategic direction of the product. This position serves as a critical bridge between raw sensor outputs and the intuitive user experience seen by farmers. Your work will directly inform how the virtual fence logic is tuned, validated, and rolled out to real-world grazing scenarios.
Key facts
- Generous leave policies include unlimited paid annual leave, wellness leave, and 6 months fully paid parental leave for primary caregivers.
- An annual $1,000 self-development budget is provided for personal growth activities.
- Visa sponsorship is not explicitly mentioned; candidates should verify eligibility to work in New Zealand.
- The hiring process requests a cover letter explaining motivation for the role and the company mission, alongside a CV.
- Halter encourages applications from candidates who may not meet every single requirement but demonstrate high potential and alignment with the mission.
What you'll do
Analyze high-frequency guidance interaction logs to identify micro-patterns in livestock movement and boundary negotiation.
Architect and maintain the data pipeline that ingests, validates, and transforms raw telemetry from the virtual fencing hardware into analysis-ready datasets.
Develop and iterate on core guidance metrics that quantify adherence, stress, and learning curves across different breeds and environments.
Partner with hardware and firmware teams to define event schemas that accurately capture the nuances of animal behavior at scale.
Design and run quasi-experimental evaluations to measure the impact of guidance algorithm changes on animal welfare and farm productivity.
Create interactive dashboards and narrative reports that translate complex statistical findings into actionable recommendations for the product team.
Implement rigorous data quality checks to ensure the integrity of spatial and temporal datasets used for long-term behavioral analysis.
Lead the documentation of the guidance data model, establishing standards for metadata, naming conventions, and data lineage.
Conduct exploratory analysis on historical pasture data to uncover seasonal trends and environmental constraints affecting virtual fence performance.
Translate ambiguous business questions into precise analytical frameworks, defining success criteria and monitoring key performance indicators over time.
Collaborate with the research farm in Morrinsville to design data collection protocols that maximize signal fidelity during live trials.
Optimize query performance on large behavioral datasets to enable rapid iteration during critical product development sprints.
Synthesize insights from cross-functional workshops to align analytical priorities with the evolving roadmap for virtual fencing features.
Mentor junior team members on best practices for data visualization, statistical reasoning, and ethical considerations in agricultural technology.
Requirements
You must possess a Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a closely related quantitative field.
You must demonstrate professional experience using Python or R for data analysis, with a portfolio or GitHub repository showcasing relevant projects.
You must have hands-on experience with SQL and at least one modern data warehouse or cloud data platform such as Snowflake, BigQuery, or Redshift.
You must be proficient in at least one data visualization tool like Tableau, Looker, or Power BI, and you must be able to craft clear, accessible dashboards.
You must have a strong grasp of statistical methods, including hypothesis testing, regression models, and experimental design principles.
You must be comfortable working with large, messy datasets and performing complex data wrangling to extract reliable signals.
You must have excellent written and verbal communication skills, enabling you to explain technical concepts to non-technical stakeholders.
You must be able to work in a hybrid role, dividing your time between an Auckland office and a rural research farm environment.
Nice to have
Experience with time-series analysis and forecasting models applied to behavioral data.
Familiarity with distributed computing frameworks or streaming data architectures.
Knowledge of livestock behavior, pasture management, or agricultural technology is appreciated.
Experience with version control workflows using Git for data science projects.
Background in A/B testing or causal inference in operational environments.
Practical notes
This is a full-time role based primarily in Auckland, with regular travel to the research farm in Morrinsville required.
The hiring process includes a cover letter detailing your motivation for the role and alignment with Halter's mission, in addition to a standard CV.
Candidates must verify their eligibility to work in New Zealand, as the company does not currently offer visa sponsorship.
The position is open to candidates who may not meet every requirement, provided they show high potential and a strong alignment with the company mission.