Data Science Specialist

This position is ideal for an experienced data science professional who excels in designing, deploying, and optimizing advanced AI solutions that deliver measurable business impact. The selected candidate will collaborate closely with clients and internal teams to translate business needs into scalable, data-driven strategies and intelligent AI systems.

• More than 5 years of experience in data science, AI, or related fields.
• Proficiency in Python, SQL, and machine learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with BI tools such as Tableau, Power BI, or similar for data visualization.
• Strong background in AI/ML techniques, including natural language processing, computer vision, and predictive analytics.
• Experience in managing a broad range of AI products and solutions as well as Generative AI (GenAI) solutions.
• Knowledge of cloud hosting environments, particularly AWS, Azure, and other relevant platforms.
• Knowledge of data warehousing concepts and ETL processes.
• Excellent problem-solving and analytical skills.
• Effective communication and client-facing skills.
• Experience in contributing to pre-sales and business development activities.
• Certifications in AI/ML, data science, or cloud platforms are a plus.
• Experience with cloud-based AI/ML platforms (e.g., AWS SageMaker, Azure ML) is a plus.
• Business proficiency level in English is a must.

• Client Collaboration: Work closely with clients to understand their business objectives, data requirements, and AI & DS needs.
• Design & Build Data Science & AI Projects: Design and implement data science and AI projects, ensuring they meet client objectives and deliver business value.
• Data Analysis and Modeling: Develop and apply advanced statistical models, machine learning algorithms, and AI techniques to solve complex business problems. Ability to adapt to the latest AI policies according to different AI systems risk levels and to make AI systems decisions transparent and interpretable.
• Cloud Hosting Expertise: Utilize knowledge of cloud hosting environments, including AWS, Azure, and other relevant platforms, to deploy and manage AI & DS solutions effectively.
• Data Integration: Integrate and analyze data from multiple sources to create unified, accurate datasets for AI & DS modeling and analysis.
• Data Visualization: Create visually appealing and interactive dashboards and visualizations to present AI & DS-driven insights in a comprehensible manner.
• Stakeholder Communication: Communicate complex AI & DS findings to non-technical stakeholders effectively.
• Pre-Sales and Business Development: Collaborate with the sales team to identify opportunities, contribute to proposal development, and present AI & DS solutions to prospective clients.