Kuku FM - Data Analyst - SQL/Python

Description :

About The Role :

We are looking for a detail-oriented Data Analyst to join our core AI/ML team.

The ideal candidate will work closely with the AI/ML Lead, business teams, and other verticals to prepare high-quality datasets, generate insights, build basic statistical/heuristic models, and support ongoing ML initiatives.

This role is perfect for someone who enjoys combining strong analytical skills with hands-on data work and business understanding.

Key Responsibilities :

Data Preparation & Analysis :

- Collect, clean, prepare, and structure data for ML training and analytical use cases.

- Perform exploratory data analysis (EDA) to identify trends, patterns, outliers, and data issues.

- Build and maintain dashboards, KPIs, and reports for product and business teams.

Support for ML Team :

- Work with the ML Lead to generate feature datasets, validate data assumptions, and evaluate model outputs.

- Build basic heuristic rules, logistic regression models, and preliminary statistical models when required.

- Conduct data validations, labeling assistance, and sampling for ML experiments.

Cross-Functional Collaboration :

- Engage with business stakeholders, product managers, and operations teams to translate requirements into data deliverables.

- Communicate insights and findings in a clear, structured manner to technical and non-technical teams.

- Act as a central resource for data-driven decision-making across multiple verticals.

Data Quality, Governance & Documentation :

- Ensure data accuracy, consistency, and completeness across datasets.

- Maintain clear documentation of data sources, definitions, and processes.

- Work with engineering teams to fix broken pipelines, incorrect metrics, or data anomalies.

Required Technical Skills :

- 1 to 3 years of experience as a Data Analyst, Business Analyst, or Associate Data Scientist.

- Strong hands-on skills in :

- SQL (advanced level)

- Python (Pandas, NumPy, basic scikit-learn)

- Excel/Google Sheets

- Experience with BI tools such as Superset

Solid understanding of :

- Descriptive statistics

- Basic probabilistic models

- Logistic regression, clustering concepts

- Ability to work with large datasets and perform efficient data wrangling.

Preferred Skills :

- Exposure to ML pipelines, feature engineering, or model evaluation basics.

- Familiarity with A/B testing, experiments, hypothesis testing.

- Experience with data warehousing tools (BigQuery, Databricks, Snowflake).

- Basic familiarity with heuristic-based decision systems or rule engines.

- Knowledge of scripting automation for recurring reports.

- Understanding of business domains like content, fintech, OTT, growth, or operations.

Preferred Tools & Technologies :

- Data Tools : SQL,Python, Pandas, NumPy

- Visualization : Tableau, Power BI, Looker

- ML Basics : Scikit-learn, Statsmodels

- Data Warehousing : BigQuery, Databricks, Athena

- Workflow : Airflow

- Version Control : Git

Education :

- Bachelors/Masters degree in Data Science, Statistics, Engineering, Computer Science, Economics, or related fields.

- Certifications in data analysis, SQL, or ML fundamentals are a plus.

What We Offer :

- Opportunity to work closely with a high-performing AI/ML team.

- Opportunity to transition into a ML engineer based on skill set, learning curve and performance.

- Exposure to end-to-end ML lifecycle : data prep ? experimentation ? deployment.

- Work on diverse problem statements across multiple business verticals.

- Competitive compensation and benefits package.

- A collaborative and growth-driven environment.

Success Metrics :

- Delivery of clean, well-structured datasets for ML model development.

- Improved data quality, reduced errors, and reliable metric reporting.

- Clear, actionable insights delivered to business and product teams.

- Efficient support for ML workflows (feature generation, sampling, validation).

- Strong documentation and repeatable processes for analytics