Open Position Open Position

Should have 4+ Years of experience in Data Scientist role.
Strong proficiency in Python programming
Good understanding of software design patterns and principles
SOLID principle, factory pattern, etc
Working knowledge of Git
Familiarity with basic Linux commands

Data analysis:

Ability to carry out exploratory data analysis (EDA) and hypothesis testing
Adept at handling large datasets, cleaning and preprocessing data, and extracting meaningful insights.
Proficiency with SQL and data visualization tools (e.g., Matplotlib, Seaborn) is important.

Model building:

In-depth knowledge of deep learning architectures, transfer learning, and experience in training and fine-tuning neural networks
In-depth knowledge of machine learning models
Proficient with ML libraries like TensorFlow, PyTorch, and scikit-learn, among others
Ability to assess model performance, interpret results, and communicate findings to non-technical stakeholders
Creativity

Model deployment:

Good understanding of API design
Ability to navigate and deploy on various cloud platforms (AWS, GCP, Azure, etc.)
Ability to design and build production model feedback loops
Ability to troubleshoot model issues in production environment
Communication skills
Communicate effectively with the internal team and clients at the right time

Responsibilities

Collaborate with clients and the internal team to understand business requirements and design AI solutions that align with their needs.
Develop and implement machine learning and deep learning models based on data analysis and experimentation to achieve project objectives.
Clean, preprocess, and transform data to ensure it's suitable for training and evaluation of AI models.
Implement AI models in production systems, considering factors like scalability, reliability, and maintainability.
Continuously monitor model performance, identify potential issues, and update models as needed to ensure they remain effective.
Stay up-to-date with the latest advancements in the AI field, and proactively suggest innovative approaches to solve complex problems.
Work closely with other teams, such as software engineers, product managers, and data engineers, to integrate AI solutions into the overall product or service.
Provide guidance and mentorship to junior data scientists in the team, fostering their professional growth.

Good to have:

DevOps / cloud infrastructure, especially with GCP/Firebase and/or AWS, Azure
Distributing workloads to compute clusters
Experience with diversity of data science problems
Experience with software development