Senior Data Scientist

Make a difference. Be happy. Grow your career.

KEY RESPONSIBILITIES

As a Senior Data Scientist with expertise in healthcare AI/ML, you will play a pivotal role in leading and overseeing the delivery of AI/ML solutions to our clients. You will be responsible for identifying and developing processes, frameworks, and tools that keep our data science team at the forefront of technological advancements. Your key responsibilities include:

• Leading the delivery of 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 to deployment.
• Establishing robust processes for creating repeatable, interpretable, dynamic, and scalable models that seamlessly integrate into analytic data products.
• Mentoring and guiding data scientists, fostering their professional growth in data science and machine learning through hands-on training and thoughtful feedback.
• 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.

JOB REQUIREMENTS

• 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.

SKILLS AND EXPERIENCE

• Bachelors in technology is required.
• Masters, Data Science, Computer Science, Engineering, or Statistics is preferred.
• Doctorate, Data Science, Computer Science, Engineering, or Statistics is preferred.
• 2+ years' experience as a senior data scientist is required
• 3+ years’ experience in healthcare data science is required
• 5+ years' experience in a data engineering, analyst, or architecture role is required.
• Technical skills: Python or R proficiency, SQL, Machine Learning concepts and engineering tools
• Programming (e.g. Python, Scala, Java), Merge and transform datasets (e.g. Databricks)
• Big Data technologies (e.g., Spark, H20.ai)
• Model deployment and maintenance
• BI tools (e.g., Tableau, PowerBI)
• Agile work process (ADO boards, Repos , Git)