Description
We are seeking a curious and analytical Data Analyst to join our growing team.
This role is the perfect blend of deep data analysis, statistical modeling, and applied machine learning.
With 3+ years of hands-on experience, you will be responsible for translating complex business questions into data-driven solutions.
You will work cross-functionally to mine massive datasets, perform exploratory data analysis, build predictive models, and generate actionable insights that drive product strategy, operational efficiency, and business growth.
The ideal candidate has a strong statistical foundation and proven experience in applying ML models to real-world business problems.
Key Responsibilities
- Exploratory Data Analysis (EDA) : Query, clean, and analyze large, complex datasets to identify trends, patterns, and anomalies.
- Predictive Modeling : Develop, train, and evaluate machine learning models (e.g., regression, classification, clustering, time-series forecasting) to solve business problems like customer churn prediction, fraud detection, or sales forecasting.
- Feature Engineering : Identify and create relevant features from raw data to improve model accuracy and performance.
- Data Manipulation : Write efficient and complex SQL queries for data extraction.
- Use Python (Pandas, NumPy) for advanced data manipulation, cleaning, and preparation.
- Insight Generation & Communication : Translate complex statistical and ML-driven findings into clear, concise, and actionable insights for non-technical stakeholders.
- Visualization : Create compelling dashboards and reports (using tools like Tableau, Power BI, or Python libraries) to communicate model results and analytical insights.
- Model Validation : Continuously monitor and validate model performance in production, suggesting improvements and retraining as needed.
- Collaboration : Partner with data engineers, product managers, and business stakeholders to define project requirements, gather data, and deploy solutions
(ref:hirist.tech)
