Data Scientist (GIS) | Consultant

ERNIis a fast-growing Software Development company headquartered and founded in Switzerland in 1994, with more than 800 employees. We are highly specialized in IT & software engineering to enable and deliver innovation in process and technology. Our first service center in Asia Pacific is in Metro Manila (Mandaluyong) from where we provide our service to Europe, APAC incl. our local market Philippines, and USA regions. We are now geared towards expansion and are looking for highly motivated joiners. WHY ERNI is the best place to call HOME? 🏡 🤩 At ERNI, this is how we can support you; ALL companyPERKS AND BENEFITStake effect UPON HIRING! Contract: there is always a project and opportunity for you. Personal Development and Travel Opportunities outside the Philippines. Baby Basket – to welcome your newborn to the ERNI family. Fruit Basket– boost of vitamins during hospitalization. Free snacks and coffee in the office 🔐 UNLOCKING NEW DOORS OF GROWTH & OPPORTUNITIES Free Training with Certifications: Grow with us through technical and non-technical training. Challenging Projects: ERNI is dedicated to developing high-quality software in complex technical environments such as MedTech, Industry, Finance, and Transportation. Have the chance to participate in various technically challenging projects amongst passionate and skilled colleagues. Employee Welfare:You will be guided by a group of people who will guide and support you to have the right tools and mindset. Promotions & Recognition:From the very first day, we offer you a way to learn and develop yourself in our company. Your colleagues and superiors consistently recognize and appreciate all efforts, making you feel satisfied with your achievements. Communication: You will find transparency, honesty, and open communication in our working culture. we value suggestions, opinions, and feedback from all employees. ⏱ FLEXIBILITY Hybrid Set-Up: We are combining both remote work and in-person work. The hybrid setup will allow you to reduce commuting time and have a more flexible work schedule. This will help you to manage better your work-life balance. 🎉EVENTS: We provide many opportunities to connect and build relationships. We are learning, growing, and celebrating achievements together. You will experience a wide range of different exciting activities. What to expect? Leisure Events, Summer Events, Family Events, Social Events, and Year-End Events. 👋 What are our wishes? What are our wishes: Minimum 8 years of professional experience in data science, advanced analytics, machine learning, geospatial analytics, or applied statistical modelling. Senior-level hands-on experience designing and delivering advanced analytics solutions for enterprise, public sector, development finance, humanitarian, agriculture, climate, infrastructure, or disaster-risk use cases. Strong experience with Python, SQL, statistical modelling, machine learning, simulation, forecasting, and analytical prototyping. Strong experience developing predictive models, classification models, clustering, anomaly detection, risk scoring, spatial prediction, scenario modelling, and decision-support tools. Hands-on experience with Monte Carlo simulation, sensitivity analysis, probabilistic forecasting, and what-if modelling for workforce, cost, financial, operational, disaster-risk, or portfolio-planning use cases. Strong experience with workforce analytics, headcount planning, salary cost forecasting, HR analytics, organizational structure analysis, vacancy analysis, or strategic workforce planning is highly desirable. Strong experience with Microsoft analytics ecosystems, including Power BI, Azure Data Lake, Microsoft Fabric, Azure Synapse, or equivalent cloud-based data platforms. Ability to design analytics-ready datasets, semantic models, KPIs, dashboards, and executive reporting products for business and technical users. Experience supporting proposal development, including reviewing RFPs, interpreting Terms of Reference, drafting technical methodologies, preparing solution approaches, and contributing to resource plans or CV-based proposal sections. Strong ability to clarify requirements directly with stakeholders and translate business questions, analytical needs, assumptions, and process rules into data science and analytics solutions. Experience with data profiling, data validation, data quality checks, model validation, assumptions documentation, and analytical QA. Strong understanding of data governance, responsible AI, metadata, lineage, privacy, security, explainability, auditability, and compliance in data-sensitive environments.Ability to work independently as the primary data science expert while collaborating with project managers, data engineers, BI developers, GIS developers, architects, and client stakeholders. Strong communication skills, with the ability to explain technical concepts, modelling assumptions, risks, trade-offs, and outputs to non-technical decision-makers. Strong documentation skills, including technical documentation, methodology notes, model assumptions, user guidance, and proposal narratives. Preferred / Nice-to-Have Qualifications Experience with ESRI GIS technologies, including ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, ArcGIS Image Analyst, ArcGIS Spatial Analyst, ArcGIS Notebooks, ModelBuilder, and ArcPy. Experience delivering GIS-related machine learning use cases such as spatial prediction, land cover classification, flood extent detection, damage assessment, exposure modelling, infrastructure risk scoring, change detection, and geospatial prioritization. Experience with remote sensing, satellite imagery, SAR data, raster analytics, vector data, spatial-temporal modelling, and geospatial feature engineering. Experience integrating GIS outputs with Power BI, Azure Data Lake, Microsoft Fabric, APIs, dashboards, web maps, or enterprise reporting tools. Experience with geospatial Python libraries such as GeoPandas, Rasterio, Xarray, Shapely, PyProj, GDAL, PostGIS, Folium, or similar. Experience with AI/ML, NLP, generative AI, responsible AI governance, model explainability, and AI-ready data foundations. Experience supporting disaster-risk management, agriculture, climate resilience, environmental reporting, infrastructure monitoring, project monitoring, or development impact analytics. Experience working with international organizations, UN agencies, development banks, government institutions, NGOs, donor-funded projects, or regulated enterprise environments. Experience supporting L2/L3 analytics issue investigation, model troubleshooting, dashboard validation, data pipeline checks, and operational support under formal SLAs. Experience with Git, CI/CD, DevOps/DataOps practices, automated testing, version control, deployment pipelines, and environment management for analytics solutions. Technical Skill Expectations Required: Python, SQL, machine learning, statistical modelling, Monte Carlo simulation, scenario modelling, forecasting, Power BI, Azure Data Lake, Microsoft Fabric or Azure Synapse, data profiling, data validation, dashboard prototyping, KPI design, model documentation, stakeholder requirements clarification, and proposal methodology writing. Strongly preferred: ESRI ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, ArcPy, ArcGIS Notebooks, geospatial ML, remote sensing, raster analytics, GIS integration, responsible AI, data governance, Git, CI/CD, and analytics solution deployment. Nice to have: ArcGIS Image Analyst, ArcGIS Spatial Analyst, SAR/flood mapping, satellite imagery analysis, object detection, change detection, PostGIS, GeoPandas, Rasterio, Xarray, NLP, generative AI, Azure Machine Learning, Databricks, Microsoft Purview, DataOps, and experience with multilateral development or donor-funded analytics projects. Work Arrangement: Employment Type: Hourly-based consultancy engagement. Working Hours: Flexible schedule within 8:00 AM – 5:00 PM. Expected Workload: Approximately 2–10 hours per week, depending on project requirements and business needs. Availability: Must be open to transitioning to a full-time engagement should the project progress to subsequent phases and require additional support.