Key skills
AWSAzureCloudNoSQLNumpyPandasPythonPyTorchScikit-LearnSQLTensorflowAIArtificial IntelligenceMachine LearningDeep LearningNLPNatural Language ProcessingComputer VisionTensorFlowscikit-learnNumPyMLOpsData EngineeringAnalyticsGoogle CloudCommunicationCritical Thinking
About this role
Role Overview
- The Artificial Intelligence Analyst will be responsible for developing, implementing, and monitoring AI
- and machine learning–based solutions.
- The professional will work on data analysis, model training, and the creation of intelligent applications that use AI to optimize processes and improve the user experience.
- In addition, it will be essential to translate concepts and ideas into functional solutions, ensuring that artificial intelligence is integrated efficiently and strategically into the company's products and services.
- Develop and implement AI models for process automation, predictive analytics, and business decision optimization.
- Create intelligent applications and systems that leverage AI to deliver innovative, personalized solutions.
- Analyze large volumes of data and identify patterns and relevant insights to enhance the company's products and services.
- Train, test, and validate machine learning models to ensure efficiency and accuracy in predictions and automations.
- Integrate AI solutions into the company's systems and platforms, ensuring compatibility and scalability.
- Stay updated on trends and innovations in the field of artificial intelligence, proposing new solutions and continuous improvements.
- Monitor the performance of AI models, tuning hyperparameters and implementing strategies to mitigate bias and prevent overfitting.
- Deliver practical, working solutions, collaborating directly with software engineering, product, marketing, and UX teams to ensure AI is effectively embedded in applications and business processes.
- Ensure AI solutions comply with regulations and ethical principles, such as data protection laws and fairness in algorithms.
- Produce technical documentation and reports on model performance and applicability within the company's processes.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Statistics, Mathematics, or related fields.
- Proven experience in developing and deploying machine learning and deep learning models.
- Strong proficiency in Python (libraries such as TensorFlow, PyTorch, Scikit-Learn, Pandas, NumPy).
- Experience handling and processing structured and unstructured data.
- Knowledge of NLP (Natural Language Processing) models, computer vision, and predictive analytics.
- Experience with SQL and NoSQL databases.
- Familiarity with cloud computing tools and platforms (AWS, Google Cloud, Azure).
- Knowledge of feature engineering techniques and hyperparameter optimization.
- Experience with MLOps (monitoring and automating AI pipelines).
- Basic understanding of information security as applied to AI.
- Experience developing applications and systems that use AI, including integration with AI APIs and mobile/web development frameworks.
- Analytical and critical thinking skills for interpreting data and developing effective solutions.
- Problem-solving skills and the ability to tackle complex challenges creatively.
- Hands-on approach, ensuring AI solutions move from concept to production and are effectively applied in the company’s products and processes.
- Clear and concise communication skills for both technical and non-technical stakeholders.
- Curiosity and continuous learning mindset, staying updated on new technologies and industry trends.
Tech Stack
- AWS
- Azure
- Cloud
- NoSQL
- Numpy
- Pandas
- Python
- PyTorch
- Scikit-Learn
- SQL
- Tensorflow