Data Scientist Remoto

The Marketing Data Scientist will analyze data and improve marketing strategies. This role utilizes techniques like predictive modeling, machine learning, and statistical analysis to understand customers, market trends, and campaign performance.

• Analyze data: Gather and analyze data from various sources, such as sales data, social media, web analytics, and CRM tools.

• Develop / Train models: Build models to predict future events.

• Identify trends: Analyze customer behavior and market trends to identify opportunities.

• Segment audiences: Group customers into segments based on their needs, desires, and aspirations.

• Optimize campaigns: Use insights to develop and implement strategies to improve marketing campaigns.

• Communicate insights: Present findings to non-technical stakeholders.

• Delivery of key Advanced Analytics/Data Science projects within time and budget.

• Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities.

• Train marketing models such as Customer Segmentation Models, Predictive Analytics Models, Market Basket Analysis, Customer Lifetime Value (CLV) Models, Churn Prediction Models, Sentiment Analysis, Marketing Mix Models (MMM), A/B Testing Frameworks, Dynamic Pricing Models, Digital Marketing Attribution Models.

The Data Scientist will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. The specific scope of this role is to develop ML solutions in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets.

This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines.

The Data Scientist will be part of a collaborative interdisciplinary team around data, where they will be responsible for the continuous delivery of statistical/ML models. They will work closely with process owners, product owners, and final business users, providing visibility and understanding of the criticality of their developments.

• Bachelor’s Degree in Computer Science or Data Science, or equivalent work experience.

• A minimum of 2 - 3 years of relevant experience.

• Experience with Azure Cloud Services, Azure Databricks, Azure Data Lake Storage, and others.

• Proficiency in SQL & Python (with knowledge of Pandas, NumPy, etc.).

• Proficiency in popular ML frameworks (Scikit-Learn, TensorFlow, or PyTorch).

• Experience with big data tools such as Spark, etc. are a big plus.

• Knowledge of the data science pipeline (end-to-end) and associated tools.

• Experience in designing and implementing data science solutions.

• Familiarity with using LLM technologies to build enterprise-wide solutions.

• Excellent interpersonal skills in dealing with internal customers at all levels in a team environment. Strong written and oral communication skills are necessary.