Data Scientist, AI & Machine Learning

Data Scientist, AI & Machine Learning at Myticas Consulting

Myticas Consulting is seeking a highly motivated Data Scientist to join our analytics and AI team. This role focuses on driving data-driven decision-making across large-scale systems and telecommunications-related use cases. You will be instrumental in advanced data analytics, machine learning modeling, and statistical analysis to extract actionable insights, build predictive systems, and support strategic business and product decisions.

Key Responsibilities

• Analyze large, heterogeneous datasets to identify patterns, trends, and insights that support business and product strategy.
• Design, develop, and deploy machine learning and statistical models to solve real-world problems (predictive analytics, classification, regression, clustering).
• Work closely with product managers, data engineers, and cross-functional teams to translate business requirements into scalable data science solutions.
• Perform exploratory data analysis, feature engineering, and model evaluation.
• Build data pipelines and integrate models into production systems where relevant.
• Communicate insights and results clearly to technical and non-technical stakeholders through visualizations and reports.
• Stay current with emerging techniques in machine learning, artificial intelligence, and data science best practices.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
• Strong programming skills in Python and experience with data science libraries (e.g., pandas, NumPy, scikit-learn).
• Experience with machine learning modeling techniques, including supervised and unsupervised methods.
• Solid statistical analysis skills and understanding of modeling assumptions and performance evaluation.
• Experience working with large datasets and data engineering tools (e.g., SQL, Spark).
• Ability to produce meaningful visualizations and presentations of analytical results.
• Strong problem-solving skills and ability to work collaboratively in cross-functional teams.

Preferred Qualifications

• Experience with big data technologies and distributed computing frameworks (e.g., Spark, Hadoop).
• Familiarity with cloud-based data platforms (AWS, Azure, GCP).
• Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch) or experience with natural language processing.
• Exposure to AI/ML model deployment workflows, MLOps tools, and CI/CD pipelines.
• Experience with real-time streaming or event-driven analytics (e.g., Kafka).

Key skills/competency

• Data Analysis
• Machine Learning
• Statistical Modeling
• Python Programming
• SQL
• Predictive Analytics
• Big Data
• Cloud Platforms
• Data Visualization
• AI/ML Deployment