Data Scientist

Role Overview

The Data Scientist at SAADAA will be responsible for leveraging data to drive actionable insights that inform business decisions. This role involves analyzing complex data sets, building predictive models, and working closely with various teams to implement data-driven strategies across marketing, product, and supply chain. The ideal candidate will have a strong analytical background, experience in machine learning, and a passion for using data to solve business challenges in a fast-paced, growth-focused environment.

WHAT WILL YOU BE RESPONSIBLE FOR?

• Data Analysis: Analyze large datasets to identify trends, patterns, and insights that support business decisions across different departments (marketing, sales, operations, etc.).
• Predictive Modeling: Develop and deploy machine learning models to predict customer behavior, optimize inventory, improve customer retention, and drive sales growth.
• Data Visualization: Create dashboards and visualizations to communicate insights effectively to non-technical stakeholders and guide strategic initiatives.
• Business Strategy Support: Collaborate with marketing, product, and supply chain teams to implement data-driven strategies and improve operational efficiency.
• Data Quality Assurance: Ensure the accuracy and consistency of data across various platforms and databases, managing data pipelines and data cleaning processes.
• A/B Testing: Design and execute A/B tests to measure the effectiveness of different business strategies, marketing campaigns, and product initiatives.
• Advanced Analytics: Apply advanced analytics techniques, including time-series analysis, regression models, and clustering algorithms, to uncover business insights and inform decisions.
• Automation: Develop automated systems to streamline data collection, processing, and reporting, enhancing overall efficiency across teams.
• Collaboration: Work closely with cross-functional teams to define business problems and deliver data-driven solutions that align with company goals.
• Continuous Learning: Stay up-to-date with the latest trends and technologies in data science, machine learning, and analytics to bring innovative solutions to the company.

WHO YOU ARE

• Experience: 2+ years of experience in data science or a related field, preferably in e-commerce, retail, or a D2C environment.
• Strong Analytical Skills: Proficient in statistical analysis and machine learning techniques to extract meaningful insights from complex data.
• Programming Skills: Advanced knowledge of Python, R, or other relevant programming languages for data analysis, along with experience in libraries such as Pandas, NumPy, SciPy, and scikit-learn.
• Data Visualization: Proficient in tools such as Tableau, Power BI, or Python libraries (Matplotlib, Seaborn) to create intuitive visualizations and dashboards.
• Machine Learning Expertise: Experience in building, training, and deploying machine learning models for classification, regression, clustering, and recommendation systems.
• SQL & Database Management: Strong proficiency in SQL and experience working with relational databases like MySQL, PostgreSQL, or NoSQL databases like MongoDB.
• Problem-Solving: Excellent problem-solving skills, with the ability to break down complex business challenges and develop data-driven solutions.
• Collaboration: Strong communication and collaboration skills, able to explain complex data insights to non-technical stakeholders.
• Business Acumen: Understanding of business operations and the ability to link data science insights to strategic business decisions.
• Attention to Detail: Meticulous with data quality and processes, ensuring that all analysis is accurate and actionable.

Qualifications

• Bachelors or Masters degree in Computer Science, Mathematics, Statistics, Engineering, or a related field.
• Strong portfolio of data science projects, including experience with machine learning models, statistical analysis, and business applications.
• Experience with cloud platforms like AWS, Google Cloud, or Azure is a plus.
• Previous experience in a fast-paced D2C, retail, or e-commerce environment is highly desirable.