Data Scientist

Key Responsibilities: • Analyze business problems to define project goals and design comprehensive end-to-end data-driven solutions. • Organize, collect, enrich, and process data from multiple touchpoints and feedback sources to support analytics and model optimization. • Perform data analysis and develop machine learning and deep learning models to predict outcomes and solve business challenges. • Lead and guide the data science team — including planning, task allocation, and ensuring timely project delivery. • Build and monitor KPI and metrics systems to evaluate model performance under various conditions (sample data, simulation, pilot, and production). • Prepare and present analytical reports and model performance summaries to management. Other Tasks: • Execute additional duties as assigned by management or department heads.

Qualifications: • Bachelor’s degree or higher in Information Technology or a related field. • Minimum 3 years of experience in data science, data analytics, or machine learning. Technical Expertise: • Strong analytical thinking, logical reasoning, and solid understanding of data structures, data organization, and data processing tools. • Deep knowledge of probability, statistical modeling, and data distribution. • Proficiency in object-oriented programming (OOP), design patterns, and strong understanding of programming fundamentals, concurrency, and distributed computing. • Skilled in at least one of the following programming languages: Java, C#, C/C++, or Python. • Proficient in database querying and experienced with at least one of the following: Oracle, MS SQL, MySQL, MongoDB, Hadoop, HBase, Cassandra, or Spark. • Familiar with data analysis tools such as Pandas, Excel, Jupyter Notebook, and Anaconda. • Hands-on experience developing or implementing machine learning algorithms (e.g., deep learning, random forest, gradient boosting) or solid theoretical understanding of ML and data analytics methods. • Skilled in data preparation, cleaning, and integration across diverse data types. • Strong understanding of software design, modularization, and system architecture. • Ability to plan and manage projects, define workflows, and break down complex problems into actionable tasks, including data flow and journey mapping. • Excellent communication and reporting skills, capable of working effectively with technical and business teams. • Self-motivated, detail-oriented, and capable of performing under pressure with strong problem-solving skills. Preferred Qualifications: • Possession of a recognized Data Scientist certification from an accredited global organization. • Prior experience handling Big Data projects or data-driven solutions for the telecommunications industry.