Senior Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Senior Data Scientist will be part of a cross-disciplinary team, working closely with other data scientists, software engineers, data engineers, data managers, product owners and Portfolio managers.

Key Accountabilities:

• Build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.
• Carry out data analyses to yield actionable business insights.
• Act as the accountable person for the statistical methods used to enquire data sets, design of Machine Learning models & defining the end-to-end data lifecycle of a data science project from ideation to production
• Translate problem statement to data architecture
• Break down data architecture requirements to tasks for other team members
• Appraise current design patterns (ex: AWS ) against requirements and adapt to the technology
• Seek / promote automated pipelines / jobs
• Communicate complex ideas in a digestible way to the business
• Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation).
• Present results to peers and senior management.
• Coach, mentor and support the data science squad on the full range of end-to-end data science and solutions development activities

Desired Criteria:

• Bachelor or master’s degree in computer science, Engineering, Informatics, Information Systems or in another quantitative fields
• Specialization in Machine Learning or Data Science will be an advantage
• 8 to 12 years with minimum of 5 to 7 years relevant experience
• Deep applied knowledge of data science tools and approaches across all data lifecycle stages.
• Detailed understanding of underlying mathematical foundations of statistics and machine learning.
• Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)
• Sophisticated SQL knowledge.
• Experience with big data technologies (e.g. Hadoop, Hive, and Spark).
• Knowledge of experimental design and analysis.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong stakeholder management and ability to influence.
• Continuous learning and improvement mindset.