About the job
Join our dynamic team at Join Makro as a Data Scientist, where your analytical skills will drive impactful decisions in the retail sector. We are looking for a passionate individual with a minimum of 2 years of experience in data science, specializing in data analysis, predictive modeling, and machine learning. Familiarity with MLOps, feature engineering, and data engineering workflows is highly advantageous.
Key Responsibilities
- Data Analysis: Gather, preprocess, and scrutinize extensive datasets to unveil trends and actionable insights that tackle retail challenges.
- Model Development: Construct, train, and implement machine learning models for applications such as demand forecasting, customer behavior analysis, and inventory optimization.
- Collaboration: Collaborate with interdisciplinary teams, including data engineers and business stakeholders, to turn requirements into data-driven solutions.
- Visualization and Communication: Effectively present insights and findings using visualizations and dashboards to enhance decision-making processes.
- Innovation: Keep abreast of the latest tools and techniques in data science and retail analytics.
Optional Responsibilities (for experienced candidates):
- Feature Engineering: Optimize and engineer features to enhance machine learning model performance, and automate feature extraction pipelines for scalable operations.
- MLOps: Engage in the deployment, monitoring, and retraining of machine learning models within production environments.
- Data Engineering: Assist in the design and maintenance of data pipelines while ensuring data integrity.
Qualifications
- Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
- Experience: Minimum of 2 years in data science or a comparable field.
- Technical Skills:
- Expertise in Python for data analysis and machine learning.
- Strong SQL capabilities for managing and querying large datasets.
- Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib).
- Soft Skills: Exceptional problem-solving, communication, and teamwork skills.
Preferred Qualifications
- Experience with MLOps tools (e.g., MLflow, Kubeflow, AWS SageMaker).
- Knowledge of data engineering tools (e.g., Apache Spark, Kafka, Airflow).
- Experience in developing real-time analytics or personalization systems.
