Data Analytics Engineer (Data Scientist)

Data Analytics Engineer (Data Scientist) for Marketing, Retention Analytics Function Job Description As a Data Analyst/Scientist, using your analytical and programming background together with your problem-solving skills, you will help extract the secrets of our data, translating data findings into customer insights. You will do so by discovering and transforming the data, performing ad-hoc data analysis, and developing data tools and dashboards for Retention team to allow them monitoring the essential metrics to identify pain points and improve business outcomes.

You are curious about data, passionate about telling stories based on data and willing to be data experts of reference within the organization. PROFESSIONAL COMPETENCIES: Passion for working in a marketing team of a B2C product and for applying data analytics to improve business results.

Professional experience in hypothesis testing, design of experiments, data mining, data visualization and data manipulation/transformation. RESPONSIBILITIES: Analyze large and complex data sets to solve a variety of business challenges using advanced statistical and analytical techniques. Leverage quantitative analysis, experimentation, data mining, and data visualization to drive business and marketing strategies.

Monitor key metrics (business measurement, testing, campaign, RCA) , set goals, forecast outcomes, and assess the effectiveness of marketing efforts to identify trends and opportunities. Develop and test strategies to optimize marketing performance, providing insights and recommendations to shape roadmaps. Collaborate with business stakeholders, engineering, and cross-functional teams to inform and implement marketing optimization strategies and guide investment decisions.

QUALIFICATIONS: Master's degree in Statistics, Econometrics, Computer Science or related quantitative fields or bachelor’s degree in Statistics, Econometrics, Computer Science, or related quantitative fields 5 years of progressive experience in a data analyst role including data mining, data transformation and delivering relevant insights. 3 years of experience in programming with SQL, Python or R for exploring and transforming data within a relational database environment. 2 years of experience on data visualization tools such as Tableau, Power BI, R Shiny, D3.js, etc. 2 years of experience on Statistical Testing (Frequentist A/B testing, Bayesian A/B testing or Multivariate testing) and design of experiments. Experience in handling large datasets in big data environments using PySpark is a bonus.

Experience working in Databricks within a cloud environment (Azure, AWS) is a bonus.

Experience with MicroStrategy, Adobe Analytics or Google Analytics. Bachelor’s degree in Mathematics, Statistics, Computer Science, or a related technical field, or equivalent practical experience. 4 years of experience in data analytics (2 years with a Ph.D.). Proficiency in large scale data query using SQL, scripting language using Python, statistical tool using R, and data visualization tools (e.g., Tableau, Power BI). Experience in designing and analyzing A/B tests to measure marketing performance. Experience on Databricks/adobe analytics/Tableau/Posit/Github will be a plus Self-starter with solid interpersonal skills.

Ensure data quality and integration across multiple sources. Communicate complex data clearly, turning insights into action. Familiarity with building data pipelines and automating analytics processes. Knowledge of messaging, product, and email marketing strategies will be a plus