As a (Senior) Consultant Data Science & AI at Statista Strategy, your primary responsibilities include acting as an expert for clients and colleagues, developing and implementing innovative business models, and crafting strategic recommendations from quantitative market models. You'll engage with top decision-makers and create actionable insights from data analyses to assist in major business decisions.

Candidates applying for the (Senior) Consultant Data Science & AI position at Statista Strategy should have a minimum of five years of experience in data science or a related field. A strong academic background in economics, IT, or natural sciences is essential, along with advanced programming skills in Python or R and experience with data science frameworks.

A successful (Senior) Consultant Data Science & AI at Statista Strategy should have excellent programming skills in Python or R, familiarity with data science frameworks like pandas and scikit-learn, and a solid understanding of version control systems like Git. Knowledge of additional programming languages such as Java or Scala is also advantageous.

Yes, collaboration is vital for the (Senior) Consultant Data Science & AI role at Statista Strategy. You will work closely with our strategy consultants and clients, fostering teamwork and operational involvement in project execution to ensure that client expectations are met and exceeded.

Statista Strategy provides a comprehensive benefits package for the (Senior) Consultant Data Science & AI position, including extensive professional development opportunities, flexible work arrangements, a mix of home office and in-office collaboration, and a support system for work-life balance among many other perks like fitness benefits and office snacks.

Highlight a project where you applied data science techniques to solve a business problem. Describe your role, the methodologies you used, the outcomes, and how it benefited the client, emphasizing your strategic involvement.

Talk about your process for conducting market research, analyzing data to identify trends, and validating assumptions. Explain how you test business model hypotheses through data analytics and real-world applications.

Specify your strengths in Python or R, and provide examples of projects where these languages helped in data analysis, model development, or delivering actionable insights to stakeholders.

Discuss your familiarity with platforms like AWS or Azure, explaining how you leveraged them in past projects for data storage, processing, or analysis, showcasing your understanding of cloud-based analytics.

Share your methods for continuous learning, whether it's through courses, webinars, industry publications, or participating in professional communities. Highlight your passion for staying at the forefront of technology.

Explain your strategy for simplifying complex data insights. Emphasize the importance of storytelling in data presentation, and how you ensured clarity and engagement for the audience.

Mention specific models like regression, decision trees, or clustering, detailing the contexts in which you’ve effectively used them to derive insights or predict outcomes based on data.

Discuss techniques you utilize to manage, clean, and analyze large datasets, including your experience with tools and frameworks like Hadoop or Spark and how they contributed to project success.

Outline your approach to teamwork, emphasizing communication tools, project management practices, and methods you employ to ensure that collaboration leads to effective outcomes.

Articulate your admiration for Statista Strategy's approach to data-driven business models, highlighting your alignment with their mission and how your skills can contribute to their innovative strategies.