Data Acquisition Analyst ( Japanese, French) - R01572719

Consultant

• Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio
• Data Science Advanced: Data Scientist

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LOCATION - 2 DAYS IN FRISCO, REST REMOTE FOR THE WEEK.

Language Skills; Japanese, French - Top 2 priorities, German, Spanish (less important).

Summary
At Brillio, we are looking for the next members of our AI teams. As our AI Training Data Acquisition Analyst, you'll help us collect, process, and analyze data from various sources and work with a team of experienced Data Scientists and Engineers to support data-driven decision-making and product development.
Join our team and help us accelerate the bridging of advanced AI technologies and customer expectations.
About The Role:

• Apply labels to collected data for the purpose of training AI models for in field scam/deepfake detections
• Perform data cleaning, validation, and transformation with analytical tools and programming languages (Python, Node).
• Extract and integrate data from various sources, such as databases, APIs, web scraping, etc.
• Communicate findings and recommendations to stakeholders using clear and concise language and visuals.
• Collaborate with data scientists and engineers to support data modeling, machine learning, and experimentation.
• Keep up to date with the latest trends and developments in data science and related fields.

About You:

• An interest in data science and willing to learn and apply new skills and tools.
• Skills in organizing data and attention to detail.
• Ability to work independently and as part of a team.
• Excellent communication and presentation skills.
• Experience with Python or similar programming language and experience with data manipulation is a plus.