Senior Data Science Specialist

Canada·WaterlooFull-Timesenior

Data ScienceData & AI

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Analyze complex datasets to determine the most effective methodologies to meet specific business needs and support executive decision-making. Model Design & Implementation: Design, implement,

Technical Tools

Data ScienceData & AI

Join Syntronic: Where Your Innovation Shapes the Future

At Syntronic, we don't just follow industry trends—we set them! Join us in partnering with visionary companies and the brightest minds to turn ground-breaking ideas into reality. Imagine working on cutting-edge telecom advancements, pioneering automotive tech, life-saving healthcare innovations, and next-gen industrial automation. Our projects are diverse, impactful, and at the forefront of technological innovation. Be a part of something extraordinary!

Who are we?:

Syntronic is a global leader in design and development, specializing in electronics, electro-mechanics, and software. We’re not just a company; we’re a community of innovators. Our teams work on projects that define the future—from creating state-of-the-art communication systems and autonomous vehicles to advancing IoT solutions that revolutionize everyday life. At Syntronic, your work will make a real difference.

What we're looking for:

We are seeking individuals who want to:

· Collaborate with top-tier clients on transformative, cutting-edge projects.

· Engage with and learn from industry leaders

· Innovate from concept to completion, ensuring high standards.

· Gain international experience on global projects.

· Thrive in an entrepreneurial environment that supports new ideas.

· Explore multiple sectors like telecommunications, automotive, healthcare, and industrial automation.

We are seeking a Senior Data Science Specialist to transform raw data into actionable business intelligence. In this role, you will leverage advanced math, statistics, and machine learning to predict trends, extract meaningful patterns, and provide strategic recommendations.

You will be responsible for the entire analytical lifecycle—from understanding business requirements to designing scalable, automated models that support data-driven decision-making across the organization.

Analytical Strategy: Analyze complex datasets to determine the most effective methodologies to meet specific business needs and support executive decision-making.

Model Design & Implementation: Design, implement, and validate ML models, hypotheses, algorithms, and experiments using predictive and prescriptive modeling techniques.

Advanced Analytics: Apply data mining, math, and statistical techniques to uncover deep-seated relationships and trends within large-scale datasets.

Data Engineering Optimization: Design efficient data loading, augmentation, and analysis techniques to ensure the accuracy and robustness of models, specifically focusing on scalability and automation.

Research & Development: Stay at the forefront of the Data Science domain, continuously identifying new tools and techniques to enhance analysis efficiency and model robustness.

Technical Ownership: Drive the end-to-end implementation of data-intensive applications and pipelines.

Total Experience: 7+ years of professional experience in a relevant data science or analytics field.

Database & Big Data: Microsoft SQL Server, Database Design, Google Cloud Platform (GCP), and BigQuery.
Data Movement: Proficient in ETL (Extract, Transform, Load) processes.
Mathematics: Strong foundation in Statistics and Advanced Analytics.

Cloud & DevOps: Experience deploying data pipelines or data-intensive applications in cloud environments using containerization and Infrastructure as Code (IaC).

Software Development: Professional experience in Java or C# development.

Web Development: Experience in web application development is a significant plus.

Experience deploying and maintaining machine learning models in production environments (MLOps), including monitoring, retraining, and performance tuning.

Hands-on experience with Python data science ecosystem (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).

Familiarity with real-time data processing and streaming frameworks (e.g., Kafka, Spark Streaming).

Experience working with large-scale, distributed data systems and optimizing performance for high-volume datasets.

Strong ability to communicate complex analytical insights to non-technical stakeholders, influencing business strategy and decisions.