Data Scientist

Employment Type: Full-time Location Type: Remote Salary: Not Specified

Position Overview

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready?

We are looking for a highly skilled Data Scientist to join our team. As a Data Scientist, you will be responsible for analyzing large amounts of raw data to extract valuable insights, building machine learning models, and contributing to data-driven decision-making processes across the organization. You will work closely with cross-functional teams, including data engineers, analysts, and business stakeholders, to turn data into actionable strategies that drive business outcomes.

The ideal candidate should have a strong background in statistical analysis, machine learning, and data mining techniques, and should be capable of translating complex datasets into understandable insights that impact business growth.

Key Responsibilities

Data Analysis and Exploration

• Analyze large, complex datasets to identify trends, patterns, and insights that inform business decisions.
• Use statistical methods to explore and interpret data, providing actionable recommendations to stakeholders.
• Identify and address data quality issues, ensuring accurate and consistent analyses.

Machine Learning and Predictive Modelling

• Build, test, and deploy predictive models and machine learning algorithms to solve business problems (e.g., customer segmentation, demand forecasting, recommendation systems).
• Continuously improve models by retraining and optimizing based on performance metrics and feedback.
• Collaborate with data engineers to integrate models into production systems for real-time decision-making.

Business Problem-Solving

• Work with business teams to define key problems and translate business objectives into data science projects.
• Develop hypotheses and design experiments to test various business scenarios using data-driven approaches.
• Present data-driven insights and recommendations to both technical and non-technical stakeholders.

Data Visualisation and Reporting

• Create clear and compelling data visualizations to communicate findings (using tools like Tableau, Power BI, or matplotlib/Seaborn).
• Design and generate dashboards and reports to help business teams track key metrics and KPIs.
• Explain complex analytical results in a clear, concise, and actionable manner to stakeholders at all levels.

Data Wrangling and Preparation

• Extract, clean, and prepare data from various internal and external sources for analysis and modeling.
• Perform data transformations, feature engineering, and scaling to optimize model performance.
• Collaborate with data engineers to design data pipelines that ensure the availability of clean, structured, and high-quality data.

Statistical and Mathematical Modelling

• Apply advanced statistical techniques, such as hypothesis testing, regression analysis, classification, and clustering, to derive insights and build models.
• Perform A/B testing, multivariate testing, and other forms of experimental design to measure the effectiveness of business interventions.

Collaboration and Stakeholder Management

• Work closely with business leaders, product teams, and other stakeholders to understand their data needs and provide them with insights that drive strategy.
• Collaborate with data engineers, analysts, and software developers to implement data solutions that align with business goals.
• Support continuous learning and knowledge sharing by presenting.

Application Instructions

Not Specified