we will keep you updated when we have similar job postings.
with a randstad account, you can:
About the Role
As a member of the Data Science & Analytics Engagement Team your will have the following responsibilities:
Bridge Between Business Users and D&A Team
- Engage with business users to understand their requirements and help them with new or existing data solutions that fulfill their needs.
...
What you'll do:
• Gain a comprehensive understanding of the business operations and the data landscape to effectively align data solutions with business needs.
• Familiarize with all existing data solutions.
• Act as a representative of the Data and Analytics team to business users, fostering strong relationships and ensuring clear communication.
• Engage with business users to gather their needs and feedback on data solutions, ensuring their requirements are met and any issues are promptly addressed.
• Manage requests from users for new data solutions or changes to existing ones, collaborating with the Data Delivery team to ensure best possible solution for the users.
• Develop prototype solutions for users when applicable, demonstrating the potential value and feasibility of new data initiatives.
• Help in adoption of data solutions within the organization, ensuring that users are aware of and effectively utilizing the available tools and resources.
• Analyze organizational data to uncover valuable insights that can inform business decisions and strategies.
• Apply statistical methods and machine learning techniques to extract meaningful patterns and trends from data, driving innovation and value creation.
Desired Skills, Knowledge, and Experience:
- Bachelor’s or master’s degree in information technology, Computer Science, or a related field.
- 3-5 years of relevant experience
- Proficiency in data analysis tools and languages such as SQL, Python, R, and data visualization tools like Tableau or Power BI. Preferably PowerBI.
- Experience with machine learning frameworks (e.g., TensorFlow, scikit-learn) and statistical analysis.
- Familiarity with data warehousing solutions and ETL (Extract, Transform, Load) processes.
- Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). Preferably Azure Data Solutions.
- Ability to align data solutions with business needs.
- Experience in translating business requirements into technical specifications and data solutions.
Good to Have:
- Strong analytical skills to interpret complex data sets and extract meaningful insights.
- Ability to identify patterns, trends, and anomalies in data to solve business problems.
- Excellent communication skills to present findings and insights effectively to both technical and non-technical stakeholders.
- Ability to work well in a team environment and collaborate with cross-functional teams.
- A strong desire to stay updated with the latest trends and advancements in data science, machine learning, and AI.
About the Role
As a member of the Data Science & Analytics Engagement Team your will have the following responsibilities:
Bridge Between Business Users and D&A Team
- Engage with business users to understand their requirements and help them with new or existing data solutions that fulfill their needs.
- Act as a representative of the D&A team, fostering strong relationships and ensuring clear communication between business users and the technical team.
Increase Adoption of Data Solutions
- Promote awareness and usage of existing data solutions among business users.
- Engage with users to gather feedback and identify opportunities for improving data solutions.
- Develop strategies to increase the adoption and effective utilization of data tools and resources within the organization.
Advanced Analytics and Innovation
- Utilize advanced analytics methods to derive valuable insights from organizational data.
= Apply statistical methods and machine learning techniques to uncover meaningful patterns and trends. ...
What you'll do:
• Gain a comprehensive understanding of the business operations and the data landscape to effectively align data solutions with business needs.
• Familiarize with all existing data solutions.
• Act as a representative of the Data and Analytics team to business users, fostering strong relationships and ensuring clear communication.
• Engage with business users to gather their needs and feedback on data solutions, ensuring their requirements are met and any issues are promptly addressed.
• Manage requests from users for new data solutions or changes to existing ones, collaborating with the Data Delivery team to ensure best possible solution for the users.
• Develop prototype solutions for users when applicable, demonstrating the potential value and feasibility of new data initiatives.
• Help in adoption of data solutions within the organization, ensuring that users are aware of and effectively utilizing the available tools and resources.
• Analyze organizational data to uncover valuable insights that can inform business decisions and strategies.
• Apply statistical methods and machine learning techniques to extract meaningful patterns and trends from data, driving innovation and value creation.
Desired Skills, Knowledge, and Experience:
- Bachelor’s or master’s degree in information technology, Computer Science, or a related field.
- 3-5 years of relevant experience
- Proficiency in data analysis tools and languages such as SQL, Python, R, and data visualization tools like Tableau or Power BI. Preferably PowerBI.
- Experience with machine learning frameworks (e.g., TensorFlow, scikit-learn) and statistical analysis.
- Familiarity with data warehousing solutions and ETL (Extract, Transform, Load) processes.
- Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). Preferably Azure Data Solutions.
- Ability to align data solutions with business needs.
- Experience in translating business requirements into technical specifications and data solutions.
Good to Have:
- Strong analytical skills to interpret complex data sets and extract meaningful insights.
- Ability to identify patterns, trends, and anomalies in data to solve business problems.
- Excellent communication skills to present findings and insights effectively to both technical and non-technical stakeholders.
- Ability to work well in a team environment and collaborate with cross-functional teams.
- A strong desire to stay updated with the latest trends and advancements in data science, machine learning, and AI.