Role Description We’re looking for a Senior or Lead Analytics Engineer to help Insight Timer learn from its data. Insight Timer is the world’s largest meditation and wellness community, with over 30 million users. You’ll work closely with product, engineering and company leaders, turning their questions into experiments, data models and insights that help people live better. This is a hands-on role with a lot of ownership. You’ll measure and interpret the experiments that decide what we ship. You’ll build the data models and metrics the whole company relies on, and you’ll use good software engineering practices to keep our data clean, trusted and easy to use. A product mindset matters here. You’re building insight that improves the app over a user’s whole lifetime, not just answering one-off questions. You’ll also help lead. As one of the most senior people in analytics, you’ll set the technical bar, mentor other analytics engineers, and help us move toward more self-serve and agentic analytics, where teams can answer their own questions and the platform does more of the work. We like to move fast and do work that matters. You’ll be trusted to make important calls and to balance speed with rigour. If you enjoy building systems that are both scalable and genuinely useful to millions of people, we’d love to talk. Key Responsibilities - A/B test analysis: Analyse and interpret experiments, and turn the results into clear recommendations for the product team. - Analytics delivery: Turn questions from the product team and company leaders into clear, useful answers, and prioritise incoming requests. - Data ingestion, modelling and metrics: Own how data comes in, how it’s modelled, and the metrics people trust. - Self-serve and agentic analytics: Build the tooling, semantic layers and agents that let the rest of the company answer their own questions. - Product and revenue analysis: Dig into behavioural and financial data to find user segments, improve conversion, and understand the consumer life cycle in the app. - Mentoring and leadership: Help grow the analytics engineering team, set technical direction, and lift the quality of what the team ships. - Communication: Explain data clearly to technical and non-technical people, and be honest about effort versus impact. - Excellent communication and interpersonal skills: Build trusted relationships with product, engineering and leadership. Qualifications - Solid experience as an analytics engineer and owning work end to end. - For the Lead level, some experience mentoring or leading others. - Strong SQL on a modern cloud warehouse (we use BigQuery, Looker and dbt). - Experience with large, event-based datasets with varied schemas. - A track record of analysing and interpreting A/B tests; causal inference is a plus. - A background in maths or statistics, or a STEM degree, is a plus. - Experience with Python, LLM or agentic analytics workflows, and semantic layers. Benefits - Competitive salaries and options. - The role is fully remote, but you must be based in Australia. - Extra leave days available for your well-being and birthday. - A generous L&D budget and wellbeing bonus. - Global company retreat every other year.

• We’re looking for a Senior or Lead Analytics Engineer to help Insight Timer learn from its data. • You’ll work closely with product, engineering and company leaders, turning their questions into experiments, data models and insights that help people live better. • This is a hands-on role with a lot of ownership. • You’ll measure and interpret the experiments that decide what we ship. • You’ll build the data models and metrics the whole company relies on, and you’ll use good software engineering practices to keep our data clean, trusted and easy to use. • A product mindset matters here. • You’re building insight that improves the app over a user’s whole lifetime, not just answering one-off questions. • You’ll also help lead. • As one of the most senior people in analytics, you’ll set the technical bar, mentor other analytics engineers, and help us move toward more self-serve and agentic analytics, where teams can answer their own questions and the platform does more of the work. • We like to move fast and do work that matters. • You’ll be trusted to make important calls and to balance speed with rigour. • If you enjoy building systems that are both scalable and genuinely useful to millions of people, we’d love to talk.

• Work with Python and Spark for large-scale data processing, using Airflow as the orchestration tool. • Own extraction and integration pipelines on AWS, operating in distributed environments such as Kubernetes and EMR. • Work on data storage and analytical layers using SQL, S3 and Trino, supporting data modeling and analytical queries. • Participate in defining and maintaining data infrastructure with Terraform, backed by a proprietary Infrastructure-as-Code (IaC) framework. • Collaborate with engineering, analytics and business teams on Spark job tuning and optimization, pipeline versioning and standardization, and contribute to platform observability, governance and scalability best practices.

Role Description ICF is seeking a Senior Climate Analytics Specialist with strong scientific programming and cloud-based, big data experience to support our broad portfolio of work on climate risk and resilience. Our projects span across commercial clients and all levels of government, enhancing the resilience of energy, transportation, and other critical infrastructure systems, and the vital societal and natural elements that make our communities whole. Our climate risk analytics leverage rigorous science, machine learning, distributed computing, and provide clear communication to enable proactive planning and implementation of resilience solutions. The consultant chosen for this position will apply advanced analytics to the analysis and interpretation of weather and climate data, contribute to the development of climate risk tools and products, and support multi-disciplinary teams on multiple short- and long-term projects. This role is ideal for candidates interested in applying advanced analytics and machine learning to novel, high-impact problems where traditional modeling approaches are insufficient and new methods must be developed. What you’ll be doing… - Serve as a technical expert on multi-disciplinary teams focused on applied climate risk and resilience projects - Use scientific programming, cloud-based distributed computing, and large-scale geospatial data processing to advance climate analytics and products - Translate complex climate risk questions into tractable analytical and modeling frameworks, selecting appropriate statistical, machine learning, and physics-informed approaches - Design, train, and rigorously validate machine learning and statistical models in data-limited and non-stationary climate contexts - Interface with clients on climate risk and resilience topics, and prepare high-quality communication materials such as presentations and reports - Complete tasks in fast-paced and self-motivated environment in a timely and efficient manner Qualifications - Bachelor's Degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar - 5+ years of relevant experience applying advanced analytics to climate, geospatial, or environmental data - 2+ years of experience with Python for processing and analyzing large, multidimensional datasets (e.g., NetCDF, Zarr), including use of Pangeo ecosystem tools such as Xarray and Dask - Demonstrated experience designing and implementing scalable, cloud-based workflows for large geospatial and climate datasets, including parallel processing, memory-aware computation, and reproducible pipelines (e.g., AWS, SageMaker) - Demonstrated experience applying machine learning and statistical models to climate science, risk analysis, or related topics, using relevant Python packages (e.g., scikit-learn, PyTorch, etc.) Requirements - Advanced degree in climate science, atmospheric science, Earth science, data science, meteorology, or similar - Ability to perform self-directed analytical work related to climate science topics and physical climate risk pertaining to energy systems, transportation networks, or other sectors - Experience working with extreme events, tail risks, or rare-event modeling in environmental or geospatial contexts - Outstanding oral and written communication skills; ability to communicate complex climate information to non-scientists to inform decision-making - Experience working with and leading multi-disciplinary teams - Organized, detail oriented, and the ability to prioritize and multi-task Benefits - Flexible workplace arrangements, work-life balance - Donation matching, volunteer opportunities - Tuition reimbursement, access to professional development resources, 401k matching, Employee Stock Purchase Plan - And many, many more (Ask your recruiter for more details!)