About Us:
As a Senior Data Scientist at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.
Technical Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, or a related field.
- Solid experience designing, developing, and implementing machine learning models using a wide range of learning paradigms including supervised, unsupervised, and reinforcement learning.
- Skilled in selecting models, engineering features, tuning hyperparameters, and assessing performance.
- Advanced proficiency in Python and key libraries such as scikit-learn, TensorFlow, PyTorch, and pandas for data handling and machine learning tasks.
- Capable of producing clean, efficient, and well-documented code.
- Strong analytical abilities for interpreting complex datasets and conducting exploratory data analysis to extract actionable insights.
- Proficient in applying statistical methods and hypothesis testing to validate findings.
- In-depth knowledge of statistical modeling techniques including regression, classification, time series analysis, and probabilistic approaches.
- Experience developing visualizations with tools like Matplotlib and Seaborn to present insights and model results clearly.
- Demonstrated capability to deploy machine learning solutions into production, ensuring their reliability and scalability.
- Familiarity with containerization and orchestration technologies is considered a plus.
- Proficient in SQL for querying, managing, and optimizing data in relational databases such as MySQL, PostgreSQL, or SQL Server.
- Experience working with cloud platforms like AWS, Google Cloud, or Azure, especially leveraging AI/ML native services.
- Familiarity with big data technologies such as Hadoop or Spark for large-scale data processing.
- Understanding of data engineering practices and tools, including ETL processes and orchestration frameworks, to support robust ML pipelines.
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Design and build scalable machine learning models to tackle complex business challenges and enhance product capabilities.
- Apply AI methodologies to analyze large datasets, identifying key trends and insights to support data-driven strategies.
- Collaborate with product managers, engineers, and analysts to transform business needs into effective data science solutions.
- Lead full-cycle deployment of machine learning models, ensuring their readiness for production and optimal performance in cloud environments.
- Perform thorough statistical modeling and data evaluation to confirm model validity and refine algorithms.
- Create and manage data visualization tools and dashboards to effectively communicate findings to diverse audiences.
- Guide and support junior data scientists, promoting a culture of continuous improvement and learning.
- Stay informed on emerging trends in machine learning and AI to strengthen the team’s technical capabilities.
- Work closely with data engineering teams to ensure high-quality, accessible data and efficient ML workflows.
- Help define and uphold best practices in data science, including reproducibility, ethical AI, and model governance.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
