Offer summary

Qualifications:

10-12+ years of experience in Data Science and Machine Learning., 5+ years of hands-on experience with Google Cloud Platform (GCP) services., Strong knowledge of Python, SQL, and machine learning frameworks like TensorFlow or PyTorch., Experience with MLOps practices and tools such as Kubeflow or MLflow..

Key responsabilities:

Design and develop machine learning models for predictive analytics and decision support.

Deploy and manage ML models using Vertex AI and BigQuery ML.

Create and optimize data pipelines and ETL workflows for model training and deployment.

Collaborate with data engineers and business teams to align models with business goals.

Job description

Hello Connections

We have an Urgent Hiring for a "Data Scientist in (British Columbia, Canada)".

Below is the Job Description.

Data Scientist w/d Strong (GCP & VertexAI)

British Columbia, Canada (Remote)

Long Term

Visa- ***Canadian Citizens & PR Only***

Experience: 10-12+ years

We are looking for a Mid-Level Data Scientist with strong expertise in Google Cloud Platform (GCP) ,Someone who has hands-on experience with Google Cloud, BigQuery and Vertex AI, Kubernetes Can design and implement advanced data models and deploy scalable machine learning solutions. The ideal candidate will have a deep understanding of data science techniques and practical experience working with GCP’s suite of cloud services.

Key Responsibilities: Data Science & Modeling:

Design and develop machine learning models for predictive analytics and decision support.
Apply advanced statistical, NLP, computer vision, and time series forecasting techniques.
Create and optimize data pipelines and ETL workflows for model training and deployment.
Cloud Implementation (GCP):
Deploy and manage ML models using Vertex AI, AI Platform, and BigQuery ML.
Build scalable data pipelines using Cloud Dataflow, Pub/Sub, and Cloud Composer (Airflow).
Use Google Cloud Storage, BigQuery, and Cloud Functions for data integration and management.
Collaborate with data engineers, cloud architects, and business teams to align models with business goals.
Translate complex data insights into actionable recommendations.
Ensure scalability, performance, and security of cloud-based data solutions.

Required Skills & Experience:

8+ years of experience in IT with Data Science and Machine Learning.
5+ years of hands-on experience with GCP cloud services.
Strong knowledge of Python, SQL, and TensorFlow/PyTorch.
Proficient in BigQuery, Vertex AI, Cloud ML Engine, and Dataflow.
Experience with MLOps practices and tools like Kubeflow, MLflow, or CI/CD pipelines.

[About Ccube]
Ccube: Pioneering Data-Driven Solutions in the Cloud
Ccube is a specialized firm that delivers measurable results across a wide range of industries by
focusing exclusively on Data and Artificial Intelligence within Cloud environments. We leverage
cutting-edge technologies and innovative strategies to help our clients harness the power of data
and achieve their business objectives.
Core Competencies:
Strategic Planning and Design of Data Systems: We collaborate with our clients to develop
comprehensive data strategies and design robust data systems that align with their business
goals. Our team of experts provides guidance on data architecture, data governance, and data
management best practices.
Development and Unification of Data Frameworks: We build and integrate data frameworks
that enable seamless data flow and analysis. Our solutions facilitate data ingestion, data
transformation, and data storage, ensuring data is readily available for business intelligence and
decision-making.
Advanced Data Analysis and Artificial Intelligence Applications: We employ sophisticated
data analysis techniques and artificial intelligence algorithms to extract valuable insights from
data. Our solutions include predictive modeling, machine learning, and natural language
processing, enabling our clients to make data-driven decisions and optimize their operations.
Cloud Computing, Data Operations, and Machine Learning Operations: We leverage the
scalability and flexibility of cloud computing to deliver efficient and cost-effective data solutions.
Our team of experts manages data operations and machine learning operations, ensuring
seamless integration and optimal performance.

Organizational Principles at Ccube:
At Ccube, we are guided by a set of core principles that shape our culture and drive our success:
Efficiency: We strive to maximize efficiency by optimizing resource utilization and streamlining
processes.
Client Satisfaction: We are committed to providing exceptional service and exceeding our clients'
expectations.
Innovation: We embrace innovation and continuously explore new technologies and approaches
to deliver cutting-edge solutions.
Humility: We maintain professional modesty and recognize that there is always room for
improvement.
Employee Advantages:
Ccube offers a stimulating and rewarding work environment with numerous benefits for our
employees:
Dynamic Startup Environment: We provide a fast-paced and entrepreneurial environment where
employees can learn, grow, and make a significant impact.
Career Growth Opportunities: We offer ample opportunities for career advancement and
professional development.
Performance-Based Incentives: We reward high-performing employees with competitive
compensation and performance-based bonuses.
Equity Participation: We offer equity participation options to eligible employees, providing them
with ownership and a stake in the company's success.
Professional Development Reimbursement: We encourage continuous learning and reimburse
employees for eligible professional development expenses.
Join Ccube and be part of a team that is shaping the future of data and AI in the cloud.

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