Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking.
Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions.
Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences.
Contribute to analytical planning and ensure alignment with overall business objectives.
Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value.
Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives.
requirements-expected :
Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing).
Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation.
Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch).
Experience leading or mentoring analytics teams and coordinating with business stakeholders.
Excellent communication skills, able to translate between technical and business perspectives effectively.
Solid understanding of business processes and data structures.
Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value.
Fluency in English for meetings with international clients.
