Data Scientist Expert
5 days ago
About Us:
SiFi is a pioneering corporate expense management platform dedicated to empowering accounting teams with seamless control over corporate spending.
We are seeking an exceptional Data Scientist to collaborate with business stakeholders, engineers, and analysts. This role involves designing and maintaining data pipelines, building data warehouses, and developing reports and dashboards to drive business decisions.
Key Responsibilities:
1. Data Management & Engineering
- Design, build, and maintain ETL/ELT data pipelines for collecting, processing, and storing structured and unstructured data.
- Develop and manage the data warehouse (DWH) architecture to ensure scalability and efficiency.
- Integrate and optimize data from multiple sources, including databases, APIs, third-party tools, and business applications.
- Evaluate data integrity, consistency, and security across all systems.
2. Business Intelligence & Reporting
- Collaborate with business teams to understand data needs and develop dashboards and reports for key performance indicators (KPIs).
- Analyze and visualize data effectively using SQL, Python, R, or BI tools.
- Provide actionable insights to drive business strategies, optimize operations, and improve customer experiences.
3. Data Science & Advanced Analytics
- Apply machine learning and statistical modeling to uncover trends, predict outcomes, and drive strategic decisions.
- Implement A/B testing frameworks and experiments to measure business impact.
- Optimize algorithms for fraud detection, customer segmentation, demand forecasting, and operational efficiency.
Requirements
- Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- 3+ years of experience in data science, analytics, or related fields.
- Strong SQL skills and experience working with relational and NoSQL databases.
- Proficiency in Python (Pandas, NumPy, Scikit-Learn, etc.) or R for data analysis and machine learning.
- Hands-on experience with ETL pipelines, data processing, and data warehousing (e.g., Snowflake, Redshift, BigQuery).
- Knowledge of cloud platforms (OCI, GCP, Azure) and experience with data tools like Airflow, DBT, Spark, or Kafka.
- Experience with BI tools (Power BI, Tableau, Looker, Metabase, etc.) for data visualization and reporting.
- Deep understanding of statistics, machine learning algorithms, and predictive modeling.
- Familiarity with big data technologies (Hadoop, Spark, Databricks, etc.).
- Knowledge of data governance, compliance, and security best practices.
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