We are looking for a skilled data scientist who can develop machine learning models/statistic models. The ideal candidate will have a strong foundation in data analysis and machine learning, with the ability to leverage web technologies to deliver user-friendly applications for data exploration and decision-making.
Responsibilities:
Conduct exploratory data analysis and develop machine learning models to derive actionable insights from diverse datasets.
Design and implement back-end systems to support data processing, model inference, and application logic.
Utilize back-end frameworks and technologies such as Flask, Django, or Fast-API to build scalable and efficient web applications.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Ensure the reliability, performance, and security of back-end systems and web applications.
Stay updated on emerging trends and advancements in data science, back-end development, and dashboard design.
Communicate findings, recommendations, and project updates to stakeholders through clear documentation, presentations, and demonstrations.
Requirements
Proven experience (3 years) in data analysis, machine learning, and statistical modeling.
Proficiency in programming languages such as Python and SQL.
Strong knowledge of back-end development frameworks/libraries such as Flask, Django, or Fast-API.
Experience with database systems (e.g., SQL, NoSQL) and data manipulation tools.
Solid understanding of software engineering principles, version control systems (e.g., Git), and agile development methodologies.
Excellent problem-solving skills and attention to detail.
Effective communication skills and the ability to work both independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
Previous experience developing dashboard interfaces for data visualization and exploration.
Familiarity with web-based visualization libraries/tools like Plotly, and Dash.
Knowledge of containerization and orchestration tools like Docker and Kubernetes.
Understanding big data technologies (e.g., Spark) and distributed computing frameworks.
Contributions to open-source projects or a strong online presence (e.g., GitHub, personal blog).