Senior Data Scientist

ERNI Mandaluyong, National Capital Region, Philippines Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team. Why ERNI is the Perfect Place for You International Exposure: Work with global clients on cutting-edge projects. Inclusive Culture: Thrive in a collaborative and diverse work environment. Career Development: Enjoy continuous learning and professional growth opportunities. Perks and Benefits Career Stability: Enjoy a stable career path with ample project opportunities. Immediate Coverage: Private HMO and insurance benefits from day one. Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites . Comprehensive Benefits: Government-mandated benefits including 13th-month pay. Skill Enhancement: Access free training and certifications. Baby Basket: To welcome your newborn to the ERNI family. Fruit Basket: Boost of vitamins during hospitalization. Office Perks: Enjoy free snacks and coffee. Growth and Opportunities Free Training: Advance your skills through technical and non-technical training. Challenging Projects: Engage in complex software projects across MedTech, Industry, Finance, and Transportation. Supportive Environment: Benefit from a team dedicated to guiding and supporting your success. Recognition and Advancement: Receive acknowledgment for your efforts and opportunities for promotion. Open Communication: Experience transparency and value your input in our culture. Flexibility Hybrid Work Setup: Balance remote and in-person work for better work-life integration. Events Connect and Celebrate: Participate in a variety of events including leisure, summer, family, social, and year-end gatherings. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related discipline . 3+ years of experience in data science, analytics, or data engineering , with hands‑on coding in R and Python . Proven experience migrating analytical pipelines from R to Python in production or enterprise environments. Strong working knowledge of Databricks , including PySpark , Delta Lake , Databricks Jobs , and Workspace management . Understanding of data modeling, feature engineering, and ETL/ELT design patterns . Proficiency with Git , notebook versioning , and collaborative development workflows. Strong grasp of statistical methods, ML modeling, and validation frameworks . Preferred: Experience deploying pipelines in Azure Databricks , AWS Databricks , or GCP Databricks environments. Familiarity with Airflow , Azure Data Factory , or Databricks Workflows for orchestration. Exposure to ML Ops practices and model lifecycle management within Databricks. Understanding of cost optimization , cluster configuration , and data governance on cloud platforms. Experience writing SQL and working with large-scale datasets . Soft Skills Analytical mindset with strong attention to detail and validation discipline. Clear communicator — able to explain data migration rationale, architecture trade‑offs, and results to technical and non‑technical audiences. Proactive, self‑driven, and comfortable in a fast‑evolving cloud and data ecosystem . Collaborative team player who thrives in cross‑functional environments spanning data science, engineering, and business teams. How can you contribute to the team? About the Role We are looking for a Data Scientist with strong expertise in R, Python, and Databricks to lead the modernization of our analytical ecosystem. In this role, you will be responsible for translating and rebuilding existing R‑based data pipelines, models, and analytical workflows into Python, optimized for execution within the Databricks Lakehouse Platform. You will play a key role in ensuring that the migration enhances scalability, maintainability, and performance while preserving analytical accuracy and business value. Key Responsibilities Analyze, document, and deconstruct existing R‑based data pipelines, scripts, and models used for analytics or reporting. Rebuild, refactor, and optimize those workflows in Python using Databricks notebooks and clusters. Leverage PySpark to handle large‑scale data transformations, aggregations, and modeling at scale. Collaborate with data engineers to integrate migrated pipelines into the broader data lakehouse architecture (Delta Lake). Ensure parity between legacy R outputs and new Python/Databricks workflows through rigorous validation and testing. Use Databricks Jobs, Workflows, and Delta Live Tables to automate and orchestrate data pipelines. Implement software engineering best practices — version control (Git), unit testing, CI/CD, and documentation. Collaborate with business analysts and domain experts to ensure model interpretability and continuity of business insights. Support data governance, quality, and reproducibility by building clean, modular, and auditable codebases. Contribute to the standardization of Python libraries, Databricks templates, and reusable components across teams. #J-18808-Ljbffr