Senior Data Scientist

Brief Description

Job Purpose Statement: The holder of this position will be responsible for managing the data science and engineering team, planning projects, and building analytics models. They should have a strong problem-solving ability and a knack for statistical analysis. The expectation for this role isto have proper understanding of the application of various tools, data mining, methodologies, statistical techniques, algorithms, and machine learning and AI principles toidentify trends, patterns, and insights from raw data. The holder will extractmeaning from data, uncover insights and identify opportunities to inform business decision making.

Detailed Description

• Managing an agile team of data scientists, machine learning engineers and big data specialists.
• Leading in modern, secure, and scalable data mining, collection, and consolidation procedures
• Leading in evaluation of Machine Learning models to ensure to ensure they achieve over 98% performance.
• Delivery of Data Analytics solutions using common data science toolkits, such as Python, SAS, R, SPSS, etc.
• Conducting EDA, data extraction, data cleaning and documentation of created models.
• Delivering projects within the allocated timeline
• Use agile scrum framework in team and projects management.
• Ensuring company-wide data quality and integrity.
• Interpreting and analyzing data problems.
• Conceiving, planning and prioritizing data projects.
• Building analytic systems and predictive models.
• Testing performance of data-driven products
• Communicating insights and discoveries from the data analytics process
• Experiment with new models and techniques
• Align data projects with organizational goals

Job Requirements

• Bachelor’s degree in computer science, Data Science or related degree
• Proven working experience as a Data Scientist, ML Engineer, and skills as in Big Data Analysis
• Machine learning skills: The Senior data scientist must have a deep understanding of machine learning techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Programming skills: The person should have strong programming skills in languages such as Python, R, or SQL, which is essential to develop and execute algorithms and models.
• Big Data Experience:  The job holder should have experience with big data technologies such as Hadoop, Spark, or NoSQL
• Data visualization: Senior data scientists should be able to use data visualization tools to communicate insights to non-technical stakeholders.
• Experience in working with Big Data Cloud solutions.
• Leadership: Strong leadership skills to manage and mentor a team of data warehouse engineers effectively (at least 2 years leading teams)
• Proper understanding of the Data Life Cycle Management
• Strong analytical skills to identify patterns and insights from large and complex data sets.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• 5 years’ experience and proven performance in design and implementation of Data Science and Analytics projects (including ML and AI projects), 2 of which were in positions managing teams and projects.

Additional Details

• Good understanding of Software Development Life Cycle process
• Good understanding of the Data Management Life Cycle
• Good understanding of Data Science methodologies