Description

Key Responsibilities
● Analyze large, complex datasets to identify trends, patterns, and insights.
● Develop and implement predictive models using statistical and machine learning techniques.
● Perform exploratory data analysis and feature engineering.
● Work closely with product, engineering, and business teams to understand their data needs and deliver actionable insights.
● Communicate findings and insights effectively to both technical and non-technical stakeholders.
● Ensure data quality and integrity by implementing data validation and cleansing processes.
● Manage and maintain databases and data pipelines.

Tool and Technology Utilization
● Utilize data science tools and technologies such as Python, R, SQL, and data visualization tools (e.g., Tableau, Power BI).
● Stay updated with the latest advancements in data science and machine learning.

Qualifications
● Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
● 3-5 years of experience in data science or a related field.
● Proven experience with statistical analysis, data mining, and predictive modeling.
● Experience working with large datasets and data visualization tools.
● Proficiency in programming languages such as Python or R.
● Strong SQL skills for database querying.
● Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn).
● Familiarity with data visualization tools (e.g., Tableau, Power BI).
● Strong understanding of data privacy and security principles.
● Ability to adapt to a fast-paced and dynamic work environment.

Preferred Qualifications
● Experience with big data technologies (e.g., Hadoop, Spark).
● Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
● Experience with A/B testing and experimental design.
● Familiarity with agile methodologies and project management tools (e.g., JIRA, Trello).

Education

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science