Senior Data Scientist

ATP; Fatih; In loco; TRY 600.000 - 1.000.000; Tempo pieno

Descrizione del lavoro

ATP is seeking a Senior Data Scientist with a PhD to lead high‑impact projects that connect advanced research with production‑ready AI applications in Turkey. You will drive end‑to‑end ML initiatives—from problem formulation and experimentation to deployment and monitoring—with strong engineering collaboration to deliver scalable solutions and measurable business value.

The role focuses on NLP, CV, robotics or related AI areas, requires Python with PyTorch or TensorFlow, and a solid background

Competenze

• PhD in Computer Science, AI, Robotics, Electrical Engineering, Statistics, Mathematics or related quantitative field with ML/AI research relevance.
• 5+ years of hands-on Data Science and ML experience.
• Strong background in NLP, CV, Robotics, Generative AI or related areas.
• Strong Python programming with PyTorch or TensorFlow, plus Pandas, NumPy and scikit-learn.
• Solid foundation in statistical modeling, hypothesis testing, experimental design and model evaluation.
• Experience preparing and analyzing datasets relevant to your specialization (text, images, video, time-series, sensor data).
• Ability to design reproducible experiments, establish baselines, and conduct error analysis.
• Understanding data leakage, overfitting, distribution shift, and robust validation practices.
• Experience balancing model quality, latency, cost, and deployment constraints.
• Strong collaboration and English communication skills.

Mansioni

• Lead end-to-end machine learning projects from problem definition to deployment and production monitoring.
• Translate business requirements into research questions, specs, and success criteria.
• Develop models and data pipelines aligned with project needs.
• Investigate methods, compare to baselines, validate improvements via controlled experiments.
• Conduct error analysis and ablations to understand model behavior.
• Collaborate with domain experts and software engineers to integrate models into products.
• Build reproducible workflows with experiment tracking, data/model versioning, testing, and documentation.
• Optimize models for production and monitor performance, reliability, and data shifts.
• Review literature, reproduce promising approaches, and assess practical value.
• Mentor junior team members and promote strong research/engineering standards.

Conoscenze

Python programming

Statistical modeling

Experiment design

Model evaluation

Data preparation

English communication

Collaboration

Formazione

PhD in Computer Science / AI / Robotics / Electrical Engineering / Statistics / Mathematics

Strumenti

PyTorch

TensorFlow

Pandas

NumPy

scikit-learn

Descrizione del lavoro

We are seeking a Senior Data Scientist with a PhD degree to lead high-impact projects that connect advanced research with production-ready AI applications.

We welcome candidates with specialist backgrounds in Natural Language Processing, Computer Vision, Robotics, or related AI disciplines. You will work across the entire development lifecycle, from problem formulation and experimentation to deployment and monitoring, combining scientific rigor with strong engineering skills to deliver reliable, scalable solutions and measurable business value.

What You’ll Bring

• A PhD in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, Statistics, Mathematics, or a related quantitative field, with research relevant to machine learning or AI.
• 5+ years of hands-on experience in Data Science and Machine Learning, including developing models for real-world applications.
• A strong research or applied background in relevant areas, such as Natural Language Processing, Computer Vision, Robotics, Generative AI, or Statistical Learning.
• Strong Python programming skills and proficiency with PyTorch or TensorFlow, alongside Pandas, NumPy, and scikit-learn.
• A solid foundation in statistical modeling, hypothesis testing, experimental design, and model evaluation.
• Experience preparing and analyzing datasets relevant to your specialization, such as text, images, video, time-series, or sensor data.
• The ability to design reproducible experiments, establish meaningful baselines, and conduct systematic error analysis.
• An understanding of data leakage, overfitting, distribution shift, and robust model validation practices.
• Experience evaluating trade-offs between model quality, inference latency, computational cost, and deployment constraints.
• Strong collaboration and communication skills, with fluency in English.

What You’ll Be Doing

• Lead end-to-end machine learning projects, from problem definition and data preparation to deployment and production monitoring.
• Translate business requirements into research questions, technical specifications, and measurable success criteria.
• Develop models and data pipelines aligned with your specialization and project needs.
• Investigate suitable methods, compare them against established baselines, and validate improvements through controlled experiments.
• Conduct error analysis and ablation studies to understand model behavior and identify opportunities for improvement.
• Collaborate with domain specialists and software engineers to integrate models into products and existing systems.
• Build reproducible development workflows using experiment tracking, data and model versioning, automated testing, and clear documentation.
• Optimize models for production and monitor their performance, reliability, and changing data conditions.
• Review scientific literature, reproduce promising approaches, and assess their practical value.
• Mentor junior team members and promote strong research and engineering standards.

Nice to Have

• Peer-reviewed publications or significant research contributions in your area of specialization.
• Experience translating doctoral research into industry applications or production systems.
• Experience with multimodal learning or collaboration across AI disciplines.
• Familiarity with model optimization, edge deployment, or cloud-based machine learning platforms.