Data Scientist

Job Requirements

. Bachelor's or Master's in Data Science, Computer Science, Statistics, Mathematics, or related field.

. Strong knowledge of statistical modeling, machine learning, and data visualization.

. Proficiency in programming languages such as Python, R, or SQL.

. Experience with big data platforms (Hadoop, Spark) and cloud environments (AWS, GCP, Azure) is a plus. . Excellent analytical thinking and problem-solving skills.

. Strong communication and storytelling skills with data.

Job Responsibility

1 Data Collection & Preparation Gather structured and unstructured data from various internal and external sources. Clean, validate, and preprocess data to ensure accuracy and consistency. Develop data pipelines for automated extraction, transformation, and loading (ETL).

2. Data Analysis & Insights Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies. Apply statistical methods and hypothesis testing to validate business assumptions. Translate data findings into actionable business insights.

3. Machine Learning & Modeling Build, train, and deploy predictive and prescriptive models using machine learning techniques. Optimize model performance and monitor accuracy over time. Apply techniques such as regression, classification, clustering, NLP, or deep learning depending on business needs.

4. Business Problem Solving Partner with stakeholders to understand business challenges and translate them into data-driven solutions. Develop dashboards and reports to visualize insights clearly for decision-makers. Support product development, customer experience, and process improvement initiatives using data.

5. Collaboration & Communication Work closely with data engineers, analysts, and business teams to ensure seamless data integration. Communicate findings in a clear and compelling way through presentations, dashboards, or reports. Provide recommendations to management based on data-driven evidence.

6. Continuous Improvement Stay updated with the latest advancements in data science, machine learning, and AI. Identify opportunities to improve data processes and model efficiency. Contribute to developing data-driven culture within the organization.