Junior Scikit-learn And Predictive Analytics Modeler

What role will you play in the team: As a Junior scikit-learn and Predictive Analytics Modeler, you will be an integral part of our core data science division, responsible for transforming raw operational data into robust predictive models. You will work alongside experienced statisticians and business intelligence experts to uncover hidden trends, build classification algorithms, and deliver quantitative insights that directly influence corporate strategic decisions.

What you will do: You will extract, cleanse, and analyze massive volumes of structured and semi-structured data using advanced SQL and Python scripts. Your primary focus will be engineering features, developing supervised and unsupervised machine learning models with scikit-learn, and validating statistical hypotheses using industry-standard analytics software to support business growth.

Key responsibility:

• Develop, validate, and deploy robust predictive models and classification algorithms utilizing Python and scikit-learn.
• Execute complex data extraction, transformation, and loading (ETL) tasks using Talend and Informatica to feed analytical models.
• Conduct rigorous statistical testing, regression analysis, and variance modeling using SAS, SPSS, and Minitab.
• Design intuitive executive dashboards and visual reports using Tableau and Power BI to communicate analytical findings clearly.
• Manage and optimize relational database schemas across PostgreSQL, MySQL, and MongoDB for high-performance querying.
• Collaborate with product and marketing teams to identify key behavioral metrics and define quantitative success criteria.
• Automate repetitive analytical workflows and data cleaning processes utilizing Make.com, Zapier Automation, and custom Python scripts.

Required Qualification and Skills:

• Degree in Applied Mathematics, Statistics, Computer Science, Economics, or quantitative discipline.
• Demonstrated proficiency in Python programming with extensive use of Pandas, NumPy, and scikit-learn.
• Strong command of SQL for advanced database querying, joins, and data aggregation across relational systems.
• Familiarity with data visualization platforms such as Tableau, Power BI, or Google Data Studio.
• Working knowledge of statistical software packages including SAS, SPSS, or Minitab.
• Strong analytical mindset with exceptional attention to detail and data integrity standards.

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  Ability to manage multiple concurrent analytical tasks in a fast-paced environment.

Benefits Included:

• Industry-leading health and life insurance plans with cashless hospitalisation benefits.
• Annual performance reviews with transparent career progression and promotion cycles.
• Generous paid time off, casual leaves, and maternity/paternity support policies.
• Sponsored access to premier online learning platforms, data science bootcamps, and certification courses.
• Well-stocked cafeteria, complimentary daily snacks, and regular recreational social gatherings.

A Day in the Life: You kick off your morning by checking automated ETL pipelines built in Talend to ensure fresh data has landed in the PostgreSQL database. Next, you dive into writing Python code to train a customer churn prediction model using scikit-learn. In the afternoon, you run diagnostic checks on your models using SPSS, update a Power BI stakeholder dashboard with the latest predictive scores, and wrap up by automating a notification workflow using Make.com.