data science analyst

3 weeks ago


Snowflake, United States Randstad Digital Portugal Full time

Randstad Digital, we are based on the excellence of our engineers, and consider our team to be our most valuable asset. Always putting talent first, we support technology specialists throughout their professional lives and ensure that they develop their skills. We provide varied and challenging career opportunities, as we work with our clients on a wide range of projects in various industries, including Automotive, Heavy Industry, Transportation, Finance, Services, Security and Biometrics, Platforms and IoT, Telecommunications, and Mobile Communications, among others. Our mission is to be a trusted digital enablement partner that facilitates the accelerated transformation of companies by providing talent, capacity, and global solutions in specialized domains. We support four service lines, including customer experience, digital and product engineering, data and analytics, and cloud transformation, as well as three engagement models, including talent services, global talent centers, and managed solutions capabilities.

your job We are seeking a talented Data Science Analyst to drive our client's success by identifying improvement opportunities in e-commerce processes. As a key member of our team, you will directly engage in performing data analysis and validation tasks, contributing to the definition and implementation of quality metrics, identification of data quality rules, and evaluation of their impact, including root cause analysis of data quality problems. Responsibilities: Perform data analysis and validation tasks to identify improvement opportunities in e-commerce processes. Contribute to the definition and implementation of quality metrics and identification of data quality rules. Validate data capture requirements in application development processes using React. Validate data lineage from capture to gold level in data lake. Facilitate data analysis initiatives, from problem identification and evaluation through to delivery, ensuring insights shape the design of products and experiences. Develop a strong understanding of all data sources available to the business, integrating these into analysis where relevant to develop a holistic understanding of the customer. Collaborate with stakeholders and UX squads to concisely define behavioral insight requirements. Experiment with customer behavior data to enable stakeholders to understand their audience and plan activity accordingly. Support high-profile complex projects spanning across multiple data sets and systems. Use analytics methods to make recommendations to Designers, Product Owners, and Managers. Apply knowledge and skills to solve the most complex analytics and quality problems. Work on multiple projects concurrently.

your profile Requirements: 4+ years of experience in data analytics/user experience analysis, with a focus on e-commerce and customer analytics. 5+ years of experience with Python and SQL. 1+ years of experience with Databricks/GCP/Snowflake. Thorough knowledge of statistical concepts (distributions, hypothesis testing, confidence intervals) and experience applying them to real-world applications. Experience (preferred) or knowledge regarding e-commerce/customer analytics concepts. Exceptional verbal and written communication skills, with the ability to engage effectively at all levels of the organization, to both technical and non-technical audiences. Excellent organizational skills and an aptitude for complex analytical and detailed work, with the ability to prioritize among multiple concurrent projects to meet deadlines. Ability to consider a broad range of issues or factors, grasp complexities, perceive relationships among problems or issues, and use accurate logic in analysis. Ability to work independently or collaboratively in a complex, rapidly changing, and culturally diverse environment. Exhibit strong initiative and a demonstrated track record of growing and learning through experience. Passion for technology and an eagerness to contribute to a team-oriented environment. Education: Bachelor’s degree in a quantitative discipline such as data science, data analytics, computer science, engineering, statistics, mathematics, finance, or other related degree. Languages: English (B2).

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