Job Description
Appedology is looking for a Jr.Data Scientist
Key Responsibilities:
Data Analysis and Exploration:
- Conduct exploratory data analysis to identify patterns, trends, and anomalies in large datasets.
- Utilize statistical methods to derive meaningful insights and make data-driven recommendations.
Model Development:
- Design and implement machine learning models for predictive and prescriptive analytics.
- Evaluate and fine-tune models to ensure optimal performance and reliability.
Feature Engineering:
- Work with data engineers to preprocess and engineer features for model development.
- Collaborate with domain experts to incorporate relevant business knowledge into the feature engineering process.
Algorithm Selection:
- Evaluate and select appropriate algorithms for specific use cases, considering factors such as accuracy, interpretability, and scalability.
Collaboration and Communication:
- Collaborate with cross-functional teams, including business analysts, engineers, and product managers, to understand business requirements and deliver actionable insights.
- Effectively communicate complex technical concepts and findings to non-technical stakeholders.
Data Visualization:
- Create clear and compelling data visualizations to communicate insights and findings to both technical and non-technical audiences.
Model Deployment:
- Work with deployment teams to deploy models into production, ensuring scalability and reliability.
Continuous Learning:
- Stay abreast of the latest developments in data science, machine learning, and relevant technologies.
- Mentor and guide junior members of the data science team.
Qualifications:
- Master’s Degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.
- Proven experience (3+ years) as a Data Scientist, with a focus on machine learning and statistical modeling.
- Strong programming skills in languages such as Python or R.
- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, sci-kit-learn).
- Solid understanding of data engineering principles and data preprocessing techniques.
- Excellent problem-solving skills and the ability to work on complex business problems independently.
- Strong communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.
- Experience with big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.