Junior Data Scientist

What role will you play in the team

As a Junior Data Scientist, you will play an instrumental role in extracting actionable insights from complex data repositories. You will bridge the gap between raw data and strategic decision-making by applying advanced statistical techniques, exploratory data analysis, and machine learning models to solve intricate business challenges for our global clientele.

What you will do

You will gather, aggregate, and analyze massive volumes of data using SQL and Python. Your day-to-day tasks will involve developing interactive dashboards in Power BI and Tableau, building statistical predictive models, and presenting data-driven recommendations to department heads to optimize operational efficiency and drive revenue growth across multiple business verticals.

Key responsibility

• Extract, transform, and load large datasets from multiple sources utilizing advanced SQL queries and ETL tools like Talend and Informatica.
• Develop comprehensive exploratory data analysis reports to uncover hidden trends, correlations, and anomalies in business metrics.
• Design and implement dynamic data visualization dashboards using Tableau and Power BI for executive leadership tracking.
• Build, validate, and deploy statistical models and machine learning algorithms using Python, R, and scikit-learn.

• Manage and query unstructured data stores using MongoDB and PostgreSQL to support data science initiatives.
• Collaborate closely with data engineering teams to optimize big data processing pipelines using Apache Spark and Hadoop.
• Conduct continuous A/B testing and statistical significance evaluations to measure the impact of newly deployed data models.

Required Qualification and Skills

• Master's or Bachelor's degree in Data Science, Statistics, Computer Science, Economics, or an equivalent quantitative field.
• Extensive practical experience programming in Python and R alongside statistical analysis software like SPSS and SAS.
• Demonstrated expertise in data visualization tools including Tableau, Power BI, and Google Data Studio.
• Comprehensive proficiency in database management systems such as SQL, MySQL, PostgreSQL, and MongoDB.
• Working knowledge of big data and streaming technologies including Apache Kafka, Hadoop, and Spark.
• Strong command over descriptive and inferential statistics, hypothesis testing, and regression modeling techniques.

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• Exceptional analytical thinking, meticulous attention to detail, and proven ability to communicate technical findings clearly.

Benefits Included

• Attractive annual compensation package that reflects top market standards for entry-level data science professionals.
• Comprehensive health insurance plan covering hospitalization, outpatient care, and wellness check-ups for employees and dependents.
• Performance-linked annual incentives, retention bonuses, and regular appraisal cycles to reward hard work.
• Generous learning and development stipend for pursuing professional certifications, workshops, and higher education.
• Modern office infrastructure featuring complimentary meals, recreational zones, cab facilities, and wellness programs.

A Day in the Life

Your day kicks off by reviewing key performance indicator trends on a custom Power BI dashboard you built. You then dive into a data extraction task using complex SQL queries to pull user behavior logs from a PostgreSQL database. In the afternoon, you run regression models in Python to test a new customer churn hypothesis, and conclude your day by sharing your analytical findings with the product management team.