Job Specifications
Working with one of our top clients, this role calls for a Data Scientist - Python / R / SQL / Azure who will design and implement predictive models, data pipelines, and BI dashboards to support strategic decision-making across multiple business domains. The successful candidate will collaborate with cross-functional teams -- including marketing, finance, supply chain, and product -- to translate complex business challenges into scalable data-driven solutions using the Microsoft Azure ecosystem.
Responsibilities:
Design, develop, and deploy machine learning and statistical models for use cases such as forecasting, demand planning, pricing, and churn prediction.
Build ETL/ELT pipelines for data ingestion, transformation, and feature engineering using Azure Data Factory, Azure Synapse, and Azure Databricks.
Work with structured and unstructured data, ensuring data quality, integrity, and governance.
Develop interactive dashboards and visualizations using Power BI, Azure Analysis Services, or similar BI tools.
Monitor, retrain, and optimize model performance to maintain reliability and accuracy.
Collaborate with data engineering and IT teams to align infrastructure with data science requirements (Azure SQL, Data Lakes, Snowflake, etc.).
Conduct statistical analysis, A/B testing, and causal inference to validate models and business hypotheses.
Document models, workflows, and methodologies to ensure reproducibility, scalability, and compliance with enterprise standards.
Provide actionable insights and recommendations that support strategic and operational initiatives.
Desired Skill Set:
Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related discipline.
3-5 years of experience as a Data Scientist or in similar advanced analytics/machine learning roles.
Strong programming proficiency in Python, R, and SQL.
Hands-on experience with Microsoft Azure tools, including Data Factory, Synapse Analytics, Databricks, Azure SQL, and Azure Machine Learning.
Solid understanding of machine learning, statistical modeling, and time series forecasting techniques.
Expertise in Power BI, including data modeling, dashboard design, and DAX calculations.
Experience designing and executing experiments or observational studies to drive data-backed business outcomes.
Excellent communication skills with the ability to translate technical analyses into clear, actionable insights for business stakeholders.
Nice to Have:
PhD or advanced degree in a quantitative discipline.
Experience with big data tools such as Spark (via Azure Databricks) and real-time data streaming technologies like Azure Event Hubs or Stream Analytics.
Familiarity with data governance, metadata management, and data privacy/compliance frameworks.
Background in CPG/FMCG, retail, or consumer goods industries.
Exposure to MLOps practices, including CI/CD, model monitoring, and automated deployment pipelines.
BeachHead is an equal opportunity agency and employer. We advocate for you and welcome anyone regardless of race, color, religion, national origin, sex, physical or mental disability, or age.
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