Data Scientist at Revent Technologies Limited

Purpose

• A talented and motivated Data Scientist with a strong background in data analysis, statistical modelling, and machine learning who is willing to work closely with cross-functional teams to leverage data to drive business decisions and optimize performance.

Key Responsibilities:

• Data Collection and Analysis: Gather, clean, and preprocess data from various sources to ensure data integrity and quality.
• Statistical Modelling: Develop and implement statistical models to identify trends, patterns, and relationships in data.
• Machine Learning: Build, train, and deploy machine learning models to solve business problems and improve decision-making processes.
• Exploratory Data Analysis: Conduct exploratory analysis to understand the characteristics and patterns present in customer data- (statistical summaries and data visualization).
• A/B Testing and Experimentation: Implement A/B tests to assess changes to recommendation algorithms and utilize data and algorithms to deliver personalized recommendations, enhancing user experiences and driving business outcomes.
• Experimentation and Hypothesis Testing: Design experiments and conduct hypothesis testing to validate assumptions, assess the impact of interventions, or optimize outcomes.
• Data Visualization: Create clear and compelling visualizations to communicate insights to stakeholders.
• Collaboration: Work with product, engineering, and business teams to understand their needs and provide data-driven solutions.
• Reporting: Generate reports and dashboards to track key metrics and performance indicators.

Qualifications:

• Education: Bachelor’s Degree or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Experience: 2 to 3 years of experience in data science, analytics, or a related field.
• Analytical Skills: Strong problem-solving abilities and attention to detail.
• Communication Skills: Excellent verbal and written communication skills to explain complex concepts to non-technical stakeholders.
• Soft Skills: Ability to work collaboratively in a team environment and manage multiple projects simultaneously.