Role Description
We are seeking a skilled and analytical
Data Scientist / Data Analyst
to join our growing data team. This entry to mid-level role is ideal for individuals with a strong foundation in data analysis and an interest in applying data science techniques to solve real-world business problems.
In this role, you will be responsible for collecting, processing, and analyzing data to generate insights, support decision-making, and contribute to data-driven strategies. You will work closely with cross-functional teams including product, marketing, operations, and engineering to turn complex data into actionable outcomes.
Key Responsibilities
Collect, clean, and organize large datasets from various sources.
Analyze data to identify trends, patterns, and insights that inform business decisions.
Build dashboards, visualizations, and reports using tools like Power BI, Tableau, or similar platforms.
Develop predictive models and statistical analyses using tools such as Python, R, or SQL.
Collaborate with stakeholders to define data requirements and translate business questions into analytical problems.
Monitor key performance indicators (KPIs) and provide regular performance updates.
Assist in implementing machine learning models or data pipelines where applicable.
Ensure data accuracy, integrity, and security in all analytical processes.
Qualifications
Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field; a Master's degree is a plus.
1–3 years of experience in data analysis, data science, or a related role.
Strong skills in SQL and data visualization tools (e.g., Power BI, Tableau, Looker).
Proficiency in Python or R for data manipulation, statistical analysis, or machine learning.
Solid understanding of statistical methods, hypothesis testing, and data modeling.
Experience with databases, APIs, or cloud-based platforms (e.g., AWS, GCP, Azure) is a plus.
Strong problem-solving skills and attention to detail.
Excellent communication skills and the ability to explain technical findings to non-technical audiences.