We are looking for a Mid-Level Data Scientist with 4-6 years of experience in managing and analyzing financial datasets. The ideal candidate should have strong expertise in data collection, cleaning, processing, and visualization, along with hands-on experience in Google BigQuery, SQL, Python or JS, Power Bi and modern BI tools. Exposure to financial datasets such as company fundamentals, technical indicators, and trading analytics will be a strong advantage.

Why Join Us?

- Innovative Work Work on exciting projects that drive transformation.

- Growth Opportunities Learning & career development opportunities.

- Collaborative Culture Be part of a skilled and passionate team.

- Competitive Salary & Perks We value your contributions!

Role & Responsibilities :

- Collect, clean, and structure large volumes of financial, trading, and operational data.

- Build and optimize data pipelines for ingestion, transformation, and storage using BigQuery and other modern tools.

- Work with structured and unstructured datasets, including company fundamentals, technical market indicators, and real-time trading data.

- Design and maintain dashboards and analytics in Power BI, Looker Studio, or similar BI platforms to provide insights for internal teams.

- Collaborate with engineering and product teams to integrate analytics seamlessly into trading applications.

- Implement and manage ETL/ELT workflows ensuring high-quality, accurate, and timely data availability.

- Conduct exploratory data analysis (EDA) and build models to derive actionable insights.

- Ensure data governance, quality checks, and compliance with industry best practices.

Skills & Qualifications :

- 4+ years of experience as a Data Scientist / Data Engineer / Analytics Specialist.

- Strong expertise in SQL and Google BigQuery for large-scale data handling.

- Proficiency in Python or JS for data analysis and processing.

- Experience with BI tools such as Power BI, Looker Studio, or Tableau.

- Familiarity with ETL/ELT workflows and data warehousing concepts.

- Hands-on experience with cloud platforms (GCP, AWS, or Azure) for data pipelines and analytics is a plus.

- Knowledge of financial datasets fundamentals, technical indicators, and trading data is a plus.

- Strong problem-solving, analytical thinking, and data storytelling skills.

- Excellent communication and collaboration abilities in a fast-paced product-driven environment.