Mid Data Scientist

Mid Data Scientist Work regime: Hybrid, Lisbon Employment type: Long-term contract We’re looking for a Mid Data Scientist ready to make a difference by crafting impactful data-driven solutions. This dynamic role offers the chance to work closely with diverse teams, developing analytical and machine learning models that create measurable business value. Required Qualifications to be successful at this role: Technical Skills: Strong knowledge of Python (NumPy, pandas, scikit-learn; with basics of PyTorch/TensorFlow). Solid experience in Exploratory Data Analysis (EDA) and feature engineering . Strong foundation in statistics and probability (hypothesis testing, inference, distributions). Proven experience building and evaluating supervised and unsupervised ML models , including tuning and validation. Knowledge of ML experimentation tools (MLflow, W&B, Databricks ML). Proficient in SQL for data analysis and querying. Understanding of model evaluation and validation strategies (cross-validation, metrics, overfitting). Basic familiarity with cloud ML platforms (Azure ML, AWS SageMaker, GCP Vertex AI). Experienced in data visualization using Matplotlib, Seaborn, Plotly , as well as BI tools like Power BI or Tableau . Understanding of MLOps fundamentals (model registry, versioning, deployment lifecycle). Soft Skills: Exceptional analytical thinking and problem-solving capabilities. Ability to clearly explain technical insights to technical and non-technical stakeholders . Collaborative mindset to ensure integration across multiple Data teams. Structured and value-oriented approach to problem-solving. Adaptable to new data, requirements, and project needs, ensuring appropriate solutions are used in varying scenarios. Takes full ownership of the analytical lifecycle and ensures the quality and reliability of models delivered. Proactive communication skills with the ability to simplify technical concepts for diverse audiences. Experience: Degree in Mathematics, Computer Science, Machine Learning , or a related field. At least 3-5 years of professional experience in data science environments, building and deploying production-level models. English proficiency (minimum B2 level). Work model: 2 days per week in the office and 3 days at home. Work schedule : At Accenture, we work under two different schedules. This work schedule provides 12 additional Compensation Days in addition to the normal holiday days. These are fixed days during national holiday periods (5 days between Christmas and New Year's Eve, 5 days during Easter, and 2 days during Carnival) During Winter (From October to May – 8 months) we work 43 hours/week : From Monday to Thursday: 09h - 19h (9 hours/day) Friday: 09h - 17h (7 Hours/day) During Summer (From June to September – 4 months) we work 39 hours/week : From Monday to Thursday: 09h - 18h (8 hours/day) Friday: 09h - 17h (7 Hours/day)