Senior 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 the retail eco-system, 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, data cleansing, data enrichment, 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.
• Perform data cleansing and enrichment to ensure data quality and usability in machine learning workflows.
• 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.
• 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 modern data science libraries and frameworks such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM, and Hugging Face Transformer
• Expertise in data cleansing and enrichment techniques to prepare high-quality datasets for analysis.
• Experience with advanced data visualization tools such as Plotly, Dash, Looker, and Superset, along with Python-based visualization libraries like Matplotlib, Seaborn, and Altair
• Familiarity with modern big data technologies such as Google Cloud Dataproc, and Data Fusion, Apache Beam, Hadoop, Spark Snowflake and distributed data processing tools
• 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, ensemble methods or large language models (LLMs)
• Experience with deployment tools and frameworks such as Docker, Kubernetes, or MLflow.
• Experience with cloud platforms like AWS, Azure, or GCP.