Advanced analytics Specialist

R0001222 Advanced analytics Specialist (Open)

We’re Nadara. We work harmoniously with the power of nature and the communities around us to power lifetimes to come. We call our approach ‘living energy’.

We don’t just produce renewable energy, we live it – recognising our relationship with the people touched by our business and supporting social, educational, cultural, and environmental initiatives that contribute to the development of the communities we work alongside.

Discover more about our business here: https://nadara.com/about/

Nadara is an innovative place to work. We work in a stimulating and challenging environment, where every day we explore the unknown with curiosity, make decisions with quality and take action and deliver with courage. For us diversity is a real value, and we encourage in connecting different perspectives with respect.

Discover more about our culture and approach here: https://nadara.com/living-the-company/

Job Description Summary:

Lead the development and delivery of advanced analytics, AI, and machine learning use cases, as well as business intelligence solutions, including the required data models, visualizations and ETL processes. This role collaborates closely with Data Analytics, AI, and Innovation teams, business stakeholders, and third-party partners to design and implement high-impact, data-driven solutions. The Advanced Analytics Specialist ensures these solutions—whether developed in-house or through external partners—drive strategic decision-making, operational efficiency, and business growth across the organization.

Job Description:

Key Responsibilities

• Lead the design, development, and delivery of advanced data analytics, artificial intelligence (AI), and machine learning (ML) solutions to drive business value, improve operational efficiency, and support data-driven decision-making.
• Manage the company’s advanced analytics use case portfolio, coordinating with internal stakeholders, suppliers, and strategic partners to ensure timely and impactful delivery.
• Build, deploy, and maintain analytical models that support strategic business objectives and enhance decision-making processes.
• Apply AI and ML techniques to feature selection, model development, fine-tuning, and implementation of predictive and prescriptive analytics systems.
• Ensure data integrity, consistency, and reliability by validating data quality throughout the analytics lifecycle.
• Analyse large and complex datasets to identify trends, patterns, and actionable insights that address key business challenges.
• Develop and optimize predictive models, machine learning algorithms, and data-driven optimization solutions tailored to business needs.
• Design and implement robust testing frameworks to validate model performance, ensure accuracy, and support continuous improvement.
• Monitor and evaluate model performance in production environments, recommending and implementing enhancements as needed.
• Oversee the industrialization and scaling of ML models across the organization, in collaboration with data engineering and data management teams.
• Partner with cross-functional teams to understand business requirements and translate them into actionable data-driven solutions, products, and use cases.
• Foster a data-driven culture within the organization through mentorship, knowledge sharing, and the development of analytics capabilities across teams.
• Collaborate with the company’s external analytics, AI, and ML partners to ensure alignment with business objectives and technical best practices.
• Support the design and development of data pipelines (ETL processes) and data management practices to ensure high-quality, reliable data for advanced analytics.
• Continuously explore and recommend new technologies, tools, and methodologies to enhance the company’s analytics and AI capabilities.

Technical skills

Mandatory skills:

• Deep understanding of AI and machine learning algorithms, including supervised, unsupervised, and reinforcement learning techniques, both for numerical data and language processing.
• Experience with model development, feature engineering, hyperparameter tuning, and deployment in production environments.
• Proficiency in advanced statistical techniques, such as regression analysis, time-series forecasting, clustering, dimensionality reduction, and hypothesis testing.
• Advanced programming skills in Python, with hands-on experience in data analytics, machine learning, and automation workflows. Knowledge of additional languages such as R, Scala or Java is an advantage.
• Practical experience with big data tools and frameworks (e.g., Apache Spark, Hadoop, Kafka), enabling large-scale data processing and real-time analytics.
• Ability to identify technical bottlenecks, optimize system performance, and recommend solutions for scalability and efficiency.
• Proficiency in working with relational (e.g., PostgreSQL, MySQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra), with strong SQL expertise for data querying, transformation, and optimization.
• Familiarity with DevOps and MLOps practices, including CI/CD pipelines, version control (e.g., Git), containerization (e.g., Docker, Kubernetes), and infrastructure as code (e.g., Terraform).
• Experience in working with data visualization tools such as Power BI, Tableau, Streamlit, and Grafana, with the ability to create compelling, interactive dashboards and reports.
• Strong skills in business communication and productivity tools, enabling effective collaboration with technical and non-technical stakeholders.

Nice-to-have skills:

• Experience with cloud computing and data platforms, such as Databricks, Snowflake or Azure Fabric.
• knowledge of data governance principles, data quality frameworks, metadata management, and compliance with data security regulations (e.g., GDPR).
• experience in developing and integrating APIs for data exchange between systems, supporting real-time and batch processing workflows.
• Awareness of emerging trends in AI, ML, and data analytics, with the ability to evaluate and adopt new tools and technologies to enhance analytical capabilities.
• Expertise in data integration methods, ETL/ELT processes, and orchestration tools like Apache Airflow, Azure Data Factory, or equivalent for efficient data pipeline management.

Business skills

• Proven leadership experience in managing advanced analytics, data science, or cross-functional teams, with the ability to inspire, mentor, and develop talent while fostering a culture of data-driven decision-making and continuous improvement.
• Strong business acumen with the ability to connect data-driven insights to strategic objectives, translating complex technical concepts into actionable recommendations that drive value creation and support business growth.
• Excellent communication skills, both written and verbal, for effectively engaging with stakeholders at all levels, including technical teams, business leaders, and external partners, while simplifying complex data for non-technical audiences.
• Strong project and program management capabilities, complemented by critical thinking and problem-solving skills, ensuring the successful delivery of analytics initiatives in dynamic, fast-paced environments.
• Demonstrated ability to collaborate with diverse cross-functional teams, aligning analytics capabilities with organizational goals, anticipating business needs, and proactively identifying opportunities for data-driven improvements.
• Results-oriented mindset with a strong sense of ownership, accountability, and autonomy, combined with adaptability and resilience to manage change, deal with uncertainty and ambiguity, and continuously improve analytics processes and outcomes.

Education and Qualifications

• Master’s degree in a STEM field or a related discipline, with a strong preference for degrees focused on Computer Science, Applied Machine Learning/AI, Mathematics, Statistics, Data Science, or other similar. A PhD in these areas is considered an advantage.
• 5+ years of professional experience in advanced analytics, data science, or related roles, with a proven track record of successfully leading analytics projects, delivering impactful use cases, or managing analytics cross‑functional teams.
• Hands-on experience in working with large, complex datasets, developing and deploying predictive models and advanced analytics solutions at scale, and delivering data-driven tools and products that drive business value.
• Demonstrated ability to collaborate effectively with cross-functional teams, translating business needs into actionable data-driven solutions that deliver measurable impact across the organization.

Location:

Lisbona

Time Type:

Full time

Worker Subtype:

Regular