Data Scientist

Make a difference. Be happy. Grow your career.

Responsible for performing general analytics and statistical modeling on existing data sets in various areas of the business (e.g., Market Economics, Supply Chain, Marketing/Advertising, Financial Services, Scientific Research, etc.). Activities include: defining data requirements, data collection, processing, cleaning, analysis, modeling and visualization. Examines and identifies data patterns and trends to help answer business questions and improve decision making. Provides inputs for complex Data Science and Big Data Mining projects. Identifies areas to increase efficiency and automation of data analysis processes.

Level: A Senior Professional (P3) applies advanced knowledge of job area typically obtained through advanced education and work experience. Responsibilities typically include: • Managing projects / processes, working independently with limited supervision. • Coaching and reviewing the work of lower level professionals. • Problems faced are difficult and sometimes complex.

Specialization Match Note: This specialization serves as a generalist role. If organization has analytics roles with specific industry/service line focus, please match to relevant sub-functions such as Actuary Analytics, Business Analytics, Customer Analytics, HR Analytics, Healthcare Analytics, etc.

Typical Title: Data Analyst

• Building data science solutions for major projects, ensuring that each initiative meets the highest standards of quality and efficiency.
• Designing and implementing end-to-end AI/ML solutions for our Nordic clients, from conceptualisation designing and building to deployment.
• Establishing robust processes for creating repeatable, interpretable, dynamic, and scalable models that seamlessly integrate into analytic data products.
• Collaborating with business partners and analytics leaders to develop innovative strategies that leverage cutting-edge AI/ML techniques and tools to achieve business objectives.
• Advocating for data-driven decision-making by educating various stakeholders on the methodologies and benefits of solving problems through data science.
• Staying actively engaged with external sources for new ideas, such as attending conferences and participating in community engagement activities, to ensure the team is informed of the latest industry trends and innovations.
• Continuously updating your knowledge and skills in data science and machine learning, including areas such as natural language processing and computer vision, to maintain a competitive edge.

• Demonstrate a meticulous eye for detail, ensuring accuracy and consistency in all tasks and deliverables.
• Identify and correct errors or inconsistencies in both written documentation and practical tasks.
• Apply logical reasoning and problem-solving skills to analyze complex situations.
• Utilize creative thinking to develop innovative solutions to challenging issues.
• Engage proactively in personal and professional development through self-study, professional courses, and industry conferences.
• Stay informed about the latest trends, technologies, and best practices relevant to the industry.
• Articulate ideas clearly and effectively through professional written correspondence such as emails, reports, and documentation.
• Exhibit strong verbal communication skills in both individual and group settings, ensuring clarity and comprehension.
• Provide exceptional service by actively listening to customer needs and addressing concerns promptly and effectively.
• Develop and maintain positive relationships with customers, ensuring high levels of satisfaction and loyalty.
• Demonstrate advanced organizational abilities to manage multiple tasks, projects, and deadlines efficiently.
• Maintain orderly Records, files, and schedules, ensuring easy retrieval and effective time management.
• Show initiative and self-motivation to work independently, managing tasks and responsibilities without constant supervision.
• Collaborate effectively with team members, contributing positively to team projects and fostering a cooperative and productive work environment.
• Possess hands-on experience in an Agile development framework, such as Scrum or Kanban.
• Participate actively in Agile ceremonies, including daily stand-ups, sprint planning, retrospectives, and reviews.
• Show adaptability in responding to changing project requirements and priorities in an Agile setting.

• Bachelor's degree in technology is required.
• A master's in data Science, Computer Science, Engineering, or Statistics is preferred.
• 3+ years' experience as a senior data scientist is required
• 2+ years’ experience in healthcare data science is required
• 1+ years' experience in a data engineering, analyst, or architecture role is required.

Nordic is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital or veteran status, or any other protected status under applicable federal, state, or local laws. We encourage individuals of all backgrounds to apply, including women, minorities, individuals with disabilities, and veterans.