Applied Data Scientist
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What you'll do
- Analyse high-frequency time-series datasets from engine diagnostics, fuel meters, and GPS systems to uncover hidden operational patterns and product opportunities.
- Design, train, and validate statistical and machine learning models tailored for anomaly detection, predictive maintenance, operational mode classification, and time-series forecasting.
- Build rapid proof-of-concept algorithms for new product features and evaluate their performance against real-world business constraints.
- Partner with backend and data engineers to translate research code into scalable, production-ready microservices and streaming pipelines.
- Develop algorithms for route classification and fleet-wide benchmarking while communicating findings clearly to product managers and client stakeholders.
What they're looking for
- Strong hands-on proficiency in Python (Pandas, NumPy, Scikit-Learn, PyTorch, or TensorFlow) paired with advanced SQL skills.
- Solid background in statistical analysis, time-series forecasting, trend decomposition, and core machine learning techniques (supervised/unsupervised learning, anomaly detection).
- Proven track record of feature engineering on large-scale continuous datasets derived from dynamic or physical systems.
- Practical experience taking models beyond Jupyter notebooks and collaborating with engineering teams to deploy them into live software features.
- Sharp analytical problem-solving skills with the ability to explain complex technical concepts clearly to non-technical partners.
Nice to have
- Prior experience handling raw IoT, telematics, or physical sensor data (GPS tracking, vibration, temperature, fluid flow rates).
- Background in industrial analytics, predictive maintenance, asset health monitoring, route classification, or maritime domain operations.
- Familiarity with modern time-series and columnar databases (ClickHouse, InfluxDB), cloud infrastructure (AWS), containerization (Docker), or MLOps frameworks.
- Experience working with geospatial data tools such as GeoPandas, Shapely, or PostGIS.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
JOB TITLE: APPLIED DATA SCIENTIST
LOCATION: CEBU CITY
WORK ARRANGEMENT: REMOTE
SHIFT: 07:00 AM-04:00 PM
COMPANY DESCRIPTION
About BSA Solutions
Come be a part of a "Great Place to Work" at BSA Solutions Inc., where we're not just offering jobs- we're building careers. With offices in both the Philippines and Malaysia, we offer a wide range of diversified roles across various industries, from accounting and IT to marketing and human resources. We are a dynamic, fast-growing company committed to nurturing an inclusive and supportive workplace culture where you can thrive. With a focus on professional development, work-life balance, and competitive benefits, we provide the perfect environment for you to grow both personally and professionally. If you are a talented professional eager to contribute to a world-class team and work with global clients, your next great career move is waiting for you right here. We are a talent outsourcing company with offices in the Philippines and Malaysia. We guide, inspire, and empower young talents to be the heroes that drive business growth. We are more than just a workplace-we are a family. We create a satisfying work environment, one where you'll look forward to coming to every day. A place where the best and brightest minds meet to build a community of successful companies.
WHAT DO WE OFFER
Financial Security: Enjoy a stable and competitive salary along with a comprehensive benefits package, including private health insurance and paid time off.
Structured Career Growth: Benefit from clear advancement opportunities, dedicated mentorship, and personalised training programs that go beyond a typical job.
Community and Support: Become part of a collaborative, dynamic team. You'll work in a supportive environment where you can build strong professional relationships and grow together.
Global Career Opportunities: Work with leading companies from around the world and gain international exposure, all from the comfort of your home country.
JOB SUMMARY
Process millions of daily telemetry data points from maritime vessels to improve operational efficiency, reduce fuel consumption, and increase vessel uptime. Seeking an Applied Data Scientist to bridge the gap between statistical modelling and product engineering by turning complex sensor data into intelligent, customer-facing platform features.
WHAT YOU’LL DO
- Analyse high-frequency time-series datasets from engine diagnostics, fuel meters, and GPS systems to uncover hidden operational patterns and product opportunities.
- Design, train, and validate statistical and machine learning models tailored for anomaly detection, predictive maintenance, operational mode classification, and time-series forecasting.
- Build rapid proof-of-concept algorithms for new product features and evaluate their performance against real-world business constraints.
- Partner with backend and data engineers to translate research code into scalable, production-ready microservices and streaming pipelines.
- Develop algorithms for route classification and fleet-wide benchmarking while communicating findings clearly to product managers and client stakeholders.
REQUIREMENTS
- Strong hands-on proficiency in Python (Pandas, NumPy, Scikit-Learn, PyTorch, or TensorFlow) paired with advanced SQL skills.
- Solid background in statistical analysis, time-series forecasting, trend decomposition, and core machine learning techniques (supervised/unsupervised learning, anomaly detection).
- Proven track record of feature engineering on large-scale continuous datasets derived from dynamic or physical systems.
- Practical experience taking models beyond Jupyter notebooks and collaborating with engineering teams to deploy them into live software features.
- Sharp analytical problem-solving skills with the ability to explain complex technical concepts clearly to non-technical partners.
Nice to Have:
- Prior experience handling raw IoT, telematics, or physical sensor data (GPS tracking, vibration, temperature, fluid flow rates).
- Background in industrial analytics, predictive maintenance, asset health monitoring, route classification, or maritime domain operations.
- Familiarity with modern time-series and columnar databases (ClickHouse, InfluxDB), cloud infrastructure (AWS), containerization (Docker), or MLOps frameworks.
- Experience working with geospatial data tools such as GeoPandas, Shapely, or PostGIS.
Ready to apply your expertise in a role that offers both stability and significant growth? If you have a passion for precision and a talent for supporting others, we want to hear from you.
Take the next step in your career and apply now to join our world-class team!
Company
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