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.