Data Scientist

NIF; Lisboa; Presencial; EUR 55 000 - 75 000; Tempo integral

Resumo da oferta

NIF in Lisboa, Portugal is seeking a Data Scientist to design and deploy advanced ML models for field operations, R&D, and autonomous systems. You will work across data pipelines, geospatial data, time series, and multi-modal datasets to support mission planning, decision making, and automation.

You will collaborate with engineers and domain experts, implement production-grade solutions, evaluate models, and document processes to ensure reliability and scalability in fast-paced environments.

Qualificações

• Bachelor’s or Master’s in Computer Science, Data Science, or related field; PhD a plus.

Responsabilidades

• Design, build, and refine ML models and data-driven solutions for real-world challenges.

Conhecimentos

Python

Time Series

Geospatial Data

ML Modeling

Deep Learning

PyTorch/TensorFlow

Hugging Face

Cloud Services

Formação académica

Bachelor's or Master's in CS/DS

PhD (preferred)

Ferramentas

GeoPandas

Rasterio

QGIS

REST APIs

Descrição da oferta de emprego

Mission:

We are seeking a skilled and motivated Data Scientist to join our team and contribute to the development, implementation, and optimization of advanced algorithms and models. Your work will support key teams such as Field Operations, R&D, Flights, Simulation, Autopilot by automating workflows and enhancing decision support, mission planning, and situational awareness capabilities.

Requirements:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. A Ph.D. is a plus.
• Experience: 3+ years of experience in data science and machine learning modeling, with a focus
• Experience in mission-critical applications such as field operations, situational awareness, or real-time systems.
• Familiarity with tools and frameworks used in geospatial analytics and drone data processing.
• On time series analysis and ideally predictive modeling.
• Strong background in machine learning, data science, and analytics, with hands-on experience in building and deploying models.
• Proven experience working with multi-modal datasets, such as sensor data as time series, GIS data, text, and unstructured data.
• Solid understanding of data pipelines, model evaluation, and production-level deployment.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Key Responsibilities:

• Design, build, and refine machine learning models and data-driven solutions to address real-world operational challenges.
• Work across the entire data science lifecycle: from problem scoping and prototyping to data annotation, model training, performance evaluation, and production deployment.
• Process and analyze diverse datasets, including but not limited to drone sensor data, geospatial (GIS) data, unstructured text, and other sensor modalities.
• Collaborate with cross-functional teams, including engineering and domain experts, to ensure seamless integration of data science solutions into production environments.
• Drive innovation through experimentation, research, and continuous improvement of existing models and systems.
• Algorithm Development: Design, develop and implement state-of-the-art algorithms and models, within the context of language models.
• Capability Development: Realize new AI-based capabilities in areas such as decision support, mission planning, workflow automation, production data support and predictive modeling and maintenance.
• Model Training and Optimization: Train and optimize models using vast amounts of textual data, ensuring high performance and accuracy.
• Data Preprocessing: Perform data preprocessing tasks such as data cleaning, outlier detection, feature scaling, and feature encoding to prepare datasets for training and evaluation.
• Research & Innovation: Stay up to date with the latest advancements in machine learning both classical techniques and deep learning and proactively apply cutting-edge methods to enhance existing models and develop innovative solutions.
• Collaboration: Work closely with data engineers, software developers, product managers and other stakeholders to understand project requirements and deliver effective solutions.
• Performance Evaluation: Evaluate the performance of models using appropriate metrics and techniques and iteratively improve their accuracy and efficiency.
• Deployment: Collaborate with engineering teams to deploy models into production environments and ensure their robustness and scalability.
• Documentation: Maintain comprehensive documentation of models, algorithms and processes for future reference and reproducibility.

Technical Skills:

• Programming & Data Manipulation: Proficient in Python, with hands-on experience using libraries such as NumPy, Pandas, SciPy, and scikit-learn for data analysis and modeling.
• Programming & Data Manipulation: Strong experience with data preprocessing, including handling of time series, unstructured, and geospatial data.
• Machine Learning & Modeling: Expertise in classical ML techniques (e.g., regression, classification, clustering) using scikit-learn, XGBoost, and other ensemble methods.
• Machine Learning & Modeling: Solid understanding of deep learning architectures for time series analysis, including Transformers, RNNs/LSTMs, and CNNs.
• Machine Learning & Modeling: Experience with model training, evaluation, and fine-tuning in varied computing environments.
• Deep Learning Frameworks: Proficient with frameworks such as PyTorch, TensorFlow, Keras, and TensorRT for building and optimizing deep learning models.
• Deep Learning Frameworks: Experience working with Hugging Face Transformers for sequence modeling and transfer learning tasks.
• Experimentation & Development Tools: Skilled in interactive experimentation environments such as Jupyter Notebooks.
• Experimentation & Development Tools: Familiarity with ML experiment tracking and versioning tools is a plus (e.g., MLflow, Weights & Biases).
• Geospatial & Sensor Data: Experience working with GIS systems, drone sensor data, and multi-modal datasets.
• Geospatial & Sensor Data: Familiarity with geospatial libraries and tools such as GeoPandas, Rasterio, QGIS, or similar is a strong advantage.
• Cloud & Deployment: Experience deploying production-grade models, including containerization and REST API integration.
• Cloud & Deployment: Familiar with cloud platforms (especially Google Cloud Platform), including ML services, storage, and serverless deployment.
• Basic understanding of DevOps practices: version control (Git), CI/CD pipelines, telemetry, monitoring, and model lifecycle management.
• Analytical Skills: Excellent analytical and problem-solving skills with the ability to design innovative solutions to complex problems.
• AI Ethics and Bias Mitigation: Experience or awareness of AI ethics, fairness and bias mitigation strategies
• Communication: Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Collaboration: Ability to work effectively in a collaborative, cross-functional team environment.
• Attention to Detail: High attention to detail and a commitment to ensuring the accuracy and quality of work.
• Adaptability: Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.

What we have to offer you:

• An excellent work environment and an opportunity to create a real impact in the world;
• A truly high-tech, state-of-the-art engineering company with flat structure and no politics;
• Working with the very latest technologies in Data & AI, including Edge AI, Swarming - both within our software platforms and within our embedded on-board systems;
• Flexible work arrangements;
• Professional development opportunities;
• Collaborative and inclusive work environment;
• Salary compatible with the level of proven experience.

Pre-Employment Requirements

Employment offers may be contingent upon successful completion of a background check and reference verification, in accordance with applicable laws and company policy.

Equal Employment Opportunity

TEKEVER is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity, and gender expression), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by federal, state, or local law.

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