Key Responsibilities
- Analyze large datasets to extract insights, build predictive models, and support data-driven decisions.
- Design and implement machine learning algorithms for classification, regression, clustering, and recommendation systems.
- Work with structured and unstructured data, performing data cleaning, pre processing, and feature engineering.
- Present findings clearly using data visualizations and dashboards (e.g., Power BI, Tableau, or Matplotlib/Seaborn).
- Collaborate with engineering and product teams to deploy models into production.
- Continuously improve models based on performance metrics and feedback.
Required Skills & Qualifications
- 6 - 10 years of experience in data science, analytics, or applied machine learning.
- Strong programming skills in Python (pandas, scikit-learn, NumPy, etc.).
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch is a plus).
- Proficient in working with SQL and relational databases.
- Experience in data visualization tools like Tableau, Power BI, or libraries like Plotly/Matplotlib.
- Experience in Warehousing or Big Query (Mandatory)
- Understanding of statistical techniques and hypothesis testing.
- Experience with cloud platforms (AWS/GCP/Azure) is a plus.
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or related field.