Data Scientist

About Us

Dropit is at the forefront of supply chain optimization, leveraging advanced technologies to enhance operational efficiency and customer satisfaction. Our mission is to seamlessly integrate AI-driven insights into existing retail systems, making impactful micro-decisions that drive macro-level improvements. Join our team and be part of an innovative journey in the retail supply chain ecosystem.

Role Overview

We are seeking a talented and motivated Data Scientist to join our team. This role is pivotal in creating, training, and deploying machine learning models that address critical aspects of the retail supply chain. The ideal candidate will have a strong background in data science, machine learning, and a deep understanding of the retail industry.

Key Responsibilities

Develop and implement machine learning models for various supply chain applications & KPIs.
Analyze real-time and historical data to identify trends, patterns, and opportunities for optimization.
Collaborate with cross-functional teams to understand business needs and translate them into data-driven solutions.
Design and conduct experiments to test hypotheses and validate model performance.
Deploy and maintain machine learning models in a production environment.
Continuously monitor and improve model performance based on feedback and new data.
Communicate findings and insights to stakeholders through clear and concise reports and presentations.
Stay up-to-date with the latest advancements in data science and machine learning, and apply them to solve complex problems.

Qualifications

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
At least 5 years of proven experience as a Data Scientist, preferably in the retail or supply chain industry.
Strong proficiency in Python and/or R, and experience with data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch.
Experience with data visualization tools like Matplotlib, Seaborn, or Tableau.
Knowledge of SQL and experience with database management.
Familiarity with big data technologies such as Hadoop, Spark, or similar.
Strong problem-solving skills and ability to think critically and creatively.
Excellent communication and teamwork skills.

Preferred Qualifications

Ph.D. in Data Science, Computer Science, Statistics, or a related field.
Experience with real-time data processing and streaming technologies.
Knowledge of advanced machine learning techniques such as deep learning, reinforcement learning, or ensemble methods.
Experience with deployment tools and frameworks such as Docker, Kubernetes, or MLflow.
Experience in deep learning or large language models (LLMs)
Experience with cloud platforms like AWS, Azure, or GCP.