Encora10

Job Title: Product Data Scientist
Key Skills: Python or R, SQL, Data
Experience: 6+ years
Location: Mexico
Mode: Remote
We at Coforge are hiring Position (17739-PE-MX-TM2-6) with the following skill set.
This role sits at the intersection of product analytics, experimentation, and data science — embedded directly with Product Management to help shape and grow our Home Improvement lending product. You’ll be the analytical backbone for a product team making high-stakes decisions about underwriting funnels, borrower experience, and growth, translating messy data into clear evidence and, where it counts, into models and instrumentation that ship. It’s a high-impact role for someone who is equally comfortable running a rigorous A/B test, writing a dbt model, and explaining a lift curve to a VP.
<h2>Responsibilities</h2>
<ul>
<li>Partner day-to-day with Home Improvement Product Managers as their embedded data science and analytics resource — turning open-ended product questions into structured analyses and clear recommendations</li>
<li>Design, run, and interpret experiments (A/B and quasi-experimental) across the borrower funnel — from offer presentment through origination — with rigor around power, sample ratio mismatch, novelty effects, and interaction risk across concurrent tests</li>
<li>Define and own the metrics framework for the Home Improvement product line: north-star and guardrail metrics, funnel and cohort definitions, and the instrumentation needed to measure them reliably</li>
<li>Work with engineering to ensure event tracking and logging are complete, accurate, and well-documented at the point of instrumentation, not discovered as gaps after the fact</li>
<li>Build and maintain data pipelines and models (e.g., SQL/dbt transformations, feature pipelines) well enough to be self-sufficient for most analyses and to collaborate credibly with data engineering on the rest</li>
<li>Develop and validate statistical and ML models supporting product decisions — response/propensity models, funnel drop-off and conversion models, segmentation, and early-stage risk or pricing signals in partnership with credit strategy — with attention to fairness, explainability, and regulatory context appropriate to a lending business</li>
<li>Bring AI fluency to the work: use LLM- and agentic-tooling to accelerate exploratory analysis, requirements gathering, and documentation, while knowing where automated outputs need human judgment and validation before they inform a decision</li>
<li>Communicate findings in a way that drives action — clear write-ups, well-chosen visualizations, and recommendations tied to specific product or roadmap decisions, not just descriptive dashboards</li>
<li>Contribute to PI planning and roadmap discussions by sizing opportunities, flagging measurement risk in proposed initiatives, and helping the team commit to work that can actually be evaluated</li>
<li>Continuously monitor product and experiment performance post-launch, and proactively surface anomalies, regressions, or new opportunities rather than waiting to be asked</li>
</ul>
<h2>Required Qualifications</h2>
<ul>
<li>5+ years of experience in a hybrid analytics/data science role (e.g., analytics consulting, product data science, applied statistics) with a track record of directly informing product decisions; bachelor’s degree or higher in a quantitative field, or equivalent combination of education and experience</li>
<li>You have strong grounding in statistics and experimentation — hypothesis testing, causal inference, experiment design, and you can explain the difference between a significant result and a meaningful one</li>
<li>You’re fluent in SQL and at least one scripting/statistical language (Python or R), and you’re comfortable enough with data engineering fundamentals (pipelines, transformations, data modeling) to build what you need and partner effectively with engineers on the rest</li>
<li>You can develop, validate, and communicate the tradeoffs of statistical and machine learning models, and you know when a simpler model or a well-designed experiment beats a complex one</li>
<li>You use AI tools in your day-to-day work — for exploratory analysis, documentation, and accelerating routine analytics — and you know when their outputs need scrutiny before they touch a product decision</li>
<li>You think like a consultant: you get to the real question behind the question, structure ambiguous problems, and land on recommendations stakeholders can act on</li>
<li>You have good judgment about rigor versus speed, and you don’t cut corners on measurement integrity just to hit a deadline</li>
<li>You’re a clear communicator who can flex between a technical conversation with engineering and a decision-focused conversation with product and business stakeholders</li>
<li>You’re curious about how data, experimentation, and AI can change what’s possible in consumer lending products, and you’re always looking for a better way to answer the question</li>
</ul>
<h2>Nice to have</h2>
<ul>
<li>Background in fintech, consumer lending, or home improvement/contractor financing</li>
<li>Experience with CDP platforms, event instrumentation tooling (e.g., Segment, mParticle, Amplitude), or experimentation platforms</li>
<li>Hands-on experience with credit or risk modeling, pricing strategy, or marketing decisioning</li>
<li>Experience with dbt, Airflow, or similar data pipeline/orchestration tools</li>
<li>Prior experience embedded directly with product teams in an agile/scrum environment</li>
</ul>
 
Posted On: September 8, 2026
At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Product Data Scientist

Título del puesto: Data Analyst
Experiencia: +3 años de experiencia afín
Ubicación: Lima, Perú
Modalidad: Híbrido, asistencia semanal (1-2 veces) y trimestral, oficina en San Isidro.
 
En Coforge estamos buscando un Data Analyst (#22483) con el siguiente perfil.
Responsabilidades principales
<ul>
<li>Diseñar y validar modelos de datos orientados a necesidades analíticas y regulatorias del negocio.</li>
<li>Analizar información de productos, procesos y datos asociados a Banca y Seguros.</li>
<li>Proponer soluciones de modelamiento de datos para iniciativas del negocio, identificando estructuras de información, reglas de negocio y oportunidades de optimización que soporten los requerimientos analíticos y operativos.</li>
<li>Participar activamente en la definición de modelos de información para nuevos requerimientos, asegurando su alineamiento con las necesidades del negocio y las mejores prácticas de gestión de datos.</li>
<li>Analizar procesos existentes desarrollados en DataStage, SSIS y AS400.</li>
<li>Participar en el levantamiento y análisis de requerimientos funcionales y de negocio.</li>
<li>Identificar y documentar métricas, indicadores y reglas de negocio requeridas por las áreas usuarias.</li>
<li>Elaborar documentos de análisis y gobierno de datos, tales como diccionarios de datos, matrices origen-destino y catálogos de indicadores.</li>
<li>Diseñar y desarrollar reportes, tableros de control e indicadores de gestión.</li>
<li>Realizar validaciones funcionales y asegurar la calidad de la información entregada a los usuarios.</li>
</ul>
Requisitos indispensables
<ul>
<li>Profesionales con +3 años de experiencia en roles de Data Analyst.</li>
<li>Experiencia en Seguros; proponiendo soluciones de modelamiento de datos para procesos y productos del sector.</li>
<li>Experiencia en modelamiento de datos (conceptual, lógico y físico).</li>
<li>Experiencia sólida con SQL Server, DB2 (deseable)</li>
<li>Experiencia con SSIS / SSAS, SSIS Catalog.</li>
<li>Conocimiento de procesos DataStage</li>
</ul>
Requisitos deseables
<ul>
<li>Conocimiento o experiencia con GeneXus, AS400 y Power BI</li>
</ul>
 
Publicado el: 24-07-2026
En Coforge, contratamos profesionales únicamente en función de sus habilidades y calificaciones, y no discriminamos en función de la edad, discapacidad, religión, género, orientación sexual, estado socioeconómico o nacionalidad.

Data Analyst (exp. en Seguros)

<div>
Job Title: Lead / Principal Data Engineer - DBT &amp; Databricks Key Skills: DBT, Azure Databricks, SQL, Python, Delta Lake, AI-Assisted Development Experience: 5+ YOE. Location: Costa Rica, Peru, Colombia, and Bolivia. Mode: Remote.
We at Coforge are hiring Lead / Principal Data Engineer - DBT &amp; Databricks (#22555) with the following skill set.
Key Responsibilities · Design, build, and maintain DBT models on Azure Databricks using Delta Lake, Unity Catalog, and Medallion Architecture principles. · Deliver curated Gold-layer data domains to production standards in regulated enterprise environments. · Leverage AI-assisted development tools such as Claude Code for model generation, refactoring, documentation, debugging, and engineering acceleration. · Establish comprehensive DBT testing strategies, including schema validation, data quality testing, unit testing, and automated quality controls. · Work within fast-paced, CI/CD-driven delivery environments using pull request workflows and automated quality gates. · Curate datasets, semantic definitions, and business terminology to support Databricks Genie and natural-language analytics initiatives. · Define and enforce data contracts, domain ownership, and governance standards. · Implement data observability, monitoring, and root-cause analysis practices across data platforms. · Drive modernization and migration initiatives through AI-assisted Data Engineering approaches. · Contribute to engineering playbooks, standards, and enablement programs related to DBT, Databricks, and AI-powered development. · Measure and improve AI-generated code adoption, quality, productivity, and delivery outcomes.
Required Skills &amp; Qualifications · 5+ years of experience in Data Engineering. · At least 2 years of hands-on experience building and operating production-grade DBT projects, including models, tests, macros, snapshots, and large-scale refactoring. · Strong SQL skills and solid Python programming experience. · Hands-on experience with Azure Databricks, including Delta Lake, Unity Catalog, and Medallion Architecture. · Strong knowledge of DBT testing frameworks, data validation, and quality assurance best practices. · Familiarity with tools such as dbt-expectations, Great Expectations, or Delta Live Tables expectations. · Experience working with Git-based pull request workflows, code reviews, and CI/CD deployment pipelines. · Experience using AI-powered development tools such as Claude Code, GitHub Copilot, Cursor, or similar solutions. · Ability to independently own data domains and collaborate directly with business stakeholders. · Strong communication, analytical, and problem-solving skills.
Preferred Skills · Experience curating Databricks Genie environments or building semantic layers for natural-language analytics. · Experience within Insurance or Financial Services domains. · Experience working with policy, claims, exposure, or regulatory reporting data. · Hands-on experience with PySpark for large-scale data transformations. · Experience with Databricks Workflows, Airflow, or similar orchestration platforms. · DBT and/or Databricks certifications. · Experience implementing AI-driven modernization and migration programs.
Posted On: 14-08-2026
At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
</div>

Lead / Principal Data Engineer - DBT & Databricks

<div>
Job Title: Senior .NET Azure AI Developer Key Skills: C#, .NET, Microsoft Azure, Azure OpenAI, Azure AI Foundry, REST APIs Experience: 5+ YOE. Location: Costa Rica, Peru, Colombia, and Bolivia. Mode: Remote.
We at Coforge are hiring Senior .NET Azure AI Developer (#22577) with the following skill set.
Key Responsibilities · Develop C# services, APIs, utilities, and reusable integration components. · Build cloud-based applications and enterprise integrations using Microsoft Azure services. · Integrate AI solutions leveraging Azure OpenAI and Azure AI Foundry. · Design and implement secure API and data integrations across cloud and internal platforms. · Build and support Copilot Studio agents integrated with Azure services, SharePoint, enterprise applications, and automation workflows. · Develop Power Automate flows for approvals, notifications, document processing, integrations, and scheduled automations. · Develop Power Apps solutions supporting business and operational processes when required. · Troubleshoot applications, APIs, integrations, permissions, workflows, and production issues. · Implement logging, monitoring, exception handling, retry mechanisms, and performance improvements. · Test, deploy, maintain, and continuously enhance AI and automation solutions. · Work independently throughout the full development lifecycle, from requirements gathering to production support.
Required Skills &amp; Qualifications · Strong hands-on experience with C# and .NET development. · Strong experience with Microsoft Azure services and cloud integrations. · Experience designing and developing REST APIs and system integrations. · Strong knowledge of JSON, SQL, authentication mechanisms, and secure data integration practices. · Hands-on experience with Azure OpenAI and Azure AI Foundry. · Experience with Git, Azure DevOps, CI/CD pipelines, and deployment processes. · Strong troubleshooting, debugging, logging, and production support skills. · Excellent problem-solving and communication skills. · Ability to work independently in a fast-paced environment.
Preferred Skills · Experience with Microsoft Copilot Studio and AI agent development. · Experience integrating SharePoint, Outlook, Teams, Dataverse, and Microsoft 365 services. · Experience developing custom connectors and enterprise integrations. · Knowledge of prompt engineering and AI model integration within business applications. · Understanding of application security, permissions, service accounts, and access control models. · Experience with Azure Application Insights or similar monitoring solutions. · Experience with Power Automate cloud flows. · Experience with Microsoft Power Apps. · Experience with UiPath or other Robotic Process Automation (RPA) platforms. · Experience with Azure Functions, Logic Apps, Service Bus, or other Azure integration services. · Python development experience is a plus.
Posted On: 14-08-2026
At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
</div>

Senior .NET Azure AI Developer

Position Title:      Machine Learning Specialist (Research &amp; Engineering)
Work Location:    BGC, Taguig City. (2 x onsite per week  hybrid set up)
 
We are seeking a versatile Machine Learning Specialist to own the end-to-end lifecycle of AI development. This role is designed for a technical expert who can navigate the entire spectrum of machine learning—from conducting state-of-the-art research and fine-tuning foundational models to architecting the production-grade pipelines and APIs that bring these models to life. You will bridge the gap between theoretical innovation and scalable business impact, ensuring our AI solutions are both cutting-edge and operationally robust.
Key Responsibilities
The following are key areas of responsibility, but not limited to the ff:
<ol>
<li>Research &amp; Experimental Innovation</li>
</ol>
<ul>
<li>Advanced Research: Conduct deep-dive research into state-of-the-art (SOTA) architectures and foundational models to solve complex business problems like credit scoring, fraud detection, and personalization.</li>
<li>Model Optimization: Execute rigorous hyperparameter tuning and fine-tuning techniques (e.g., PEFT, LoRA, QLoRA) to maximize model accuracy and efficiency.</li>
<li>Benchmarking &amp; Evaluation: Develop comprehensive evaluation frameworks and leaderboards to monitor model accuracy and compare experimental iterations.</li>
</ul>
<ol>
<li>Data Strategy &amp; Engineering</li>
</ol>
<ul>
<li>Pipeline Design: Lead the design of experimentation datasets and production data pipelines, focusing on feature engineering and data augmentation.</li>
<li>Data Quality: Ensure high-quality data inputs for both training and real-time inference, collaborating with data squads to maintain data integrity.</li>
</ul>
<ol>
<li>Production Engineering &amp; MLOps</li>
</ol>
<ul>
<li>Deployment &amp; Orchestration: Architect and manage the end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.</li>
<li>System Integration: Build robust APIs to integrate AI models with internal platforms and refactor research code into production-grade, low-latency, and high-throughput codebases.</li>
<li>Model Governance: Implement MLOps best practices, including versioning (DVC), drift detection, and automated "quality gates" to ensure alignment with internal KPIs and regulatory standards.</li>
</ul>
<ol>
<li>Squad Collaboration &amp; Agile Delivery</li>
</ol>
<ul>
<li>Active Squad Collaboration: Work as a core member of a cross-functional squad, aligning daily with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration.</li>
<li>Agile Participation: Drive technical value within Agile ceremonies (Stand-ups, Sprints, Retrospectives) by translating high-level business requirements into executable research hypotheses and production-ready sprints.</li>
</ul>
<ol>
<li>Documentation &amp; Knowledge Leadership</li>
</ol>
<ul>
<li>Technical Documentation: Author and maintain the full technical stack documentation, ranging from scientific research findings and experimental logs to system architecture diagrams and deployment guides.</li>
<li>Peer Mentoring: Act as a technical subject matter expert by mentoring squad members, conducting code reviews, and fostering an internal culture of AI literacy and "New Ways of Working."</li>
</ul>
Minimum Requirements
<ul>
<li>Education: Undergraduate degree in a quantitative field (e.g., Computer Science, Statistics,Information Technology or Physics, or Mathematics). A Graduate degree (Master’s or PhD) is highly preferred for the research component.</li>
<li>Experience: 3+ years in a functionally similar role (Data Science, ML Research, or ML Engineering).</li>
<li>Technical Proficiency: * Expert-level Python and SQL.</li>
<ul>
<li>Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX).</li>
<li>Hands-on experience with Git, CI/CD, and MLOps tools.</li>
</ul>
<li>Mindset: A strong bias toward model explainability and security.</li>
</ul>
Preferred Skills
<ul>
<li>Portfolio: A demonstrable portfolio of advanced AI use cases (e.g., GenAI, NLP, Recommender Systems, or Graph Algorithms).</li>
<li>Cloud Infrastructure: Familiarity with AWS, GCP, or Azure AI services.</li>
<li>Publications: Published research in relevant AI/ML conferences or journals.</li>
</ul>

Encora10

Open jobs at Encora10

Product Data Scientist

Data Analyst (exp. en Seguros)

Lead / Principal Data Engineer - DBT & Databricks

Senior .NET Azure AI Developer

Machine Learning Specialist

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