As a member of the Data Science team, you will work on cutting-edge customer projects across diverse areas such as product recommendations, fraud detection, supply chain optimization, and demand forecasting.Full of energy, fresh ideas, and ambition, you are someone who loves learning new things, welcomes challenges, and has the confidence to challenge us too. We are seeking recent graduates (with less than one year of post-graduation experience) who bring enthusiasm, creativity, and business acumen to drive real innovation and become our future leaders.In this role, you should be highly analytical, with a strong foundation in mathematics, statistics, and data analysis. Critical thinking and problem-solving skills are essential for interpreting data, and a passion for machine learning and research is highly valued.Your goal will be to help our customers analyze trends and make better, data-driven decisions.If you get a thrill working with cutting-edge technology and love to help solve customers’ problems, we’d love to hear from you. It’s time to rethink the possible. Are you ready?
What you will be doing
- Develop analytical models to generate insights that improve business decision-making.
- Experiment with and implement machine learning techniques on internal and external customer projects.
- Continuously learn new data science techniques and programming languages, and assess their applicability to ongoing projects.
- Contribute to team discussions by providing insights on current approaches and methodologies.
- Follow established MLOps practices in model development and deployment.
- Participate in data science model selection, implementation, and evaluation.
- Work independently while collaborating effectively within a team environment.
- Take ownership of tasks and deliver results on schedule with minimal supervision
Qualifications and skills
- Bachelor's degree in computer science, Information Technology, or a related field.
- Proficiency in machine learning and statistical analysis.
- Knowledge of classification (e.g., random forest, logistic regression), regression (e.g., linear, XGBoost), and clustering (e.g., k-means) techniques.
- Experience in software development.
- Proficient in Python, R, SAS, SQL, data visualization tools (e.g., Tableau, Power BI), deep learning frameworks, and Spark.
- Excellent written and verbal communication skills.
- Experience with cloud computing platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure (preferred but not required).
- Hands-on participation in multiple data science projects.
- Familiarity with a range of data science methodologies.
- Strong attention to detail.
- Ability to manage multiple tasks effectively.
- Strong analytical and problem-solving skills.
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