Data Analyst - AI/ML

Assent

2 - 4 years

11 - 15 Lacs

pune

Posted:Just now| Platform:

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Skills Required

computer science data analysis metadata manager quality assurance business analytics analytical data quality reporting tools sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Data Discovery & Knowledge Building: Interview teams across the organization to understand what data they use, where it resides, and how it is accessed.
Data Inventory & Documentation: Build and maintain a central inventory of datasets, including metadata, ownership, quality checks, and access details.
SQL & Python Analysis: Query, clean, and analyze datasets to support exploratory data analysis (EDA), model development, feature engineering, and validation.
Apply data cleaning, transformation, and interpolation techniques to handle missing, inconsistent, or incomplete datasets, ensuring reliable downstream use.
Insights & Dashboards: Develop reports and dashboards in Tableau, and Sigma to track data quality, dataset usage, and AI/ML performance metrics.
Ad-hoc Support: Provide on-demand analyses to support AI/ML experiments, audits, and evaluations.
Data Quality Assurance: Monitor and flag issues in data accuracy, completeness, and consistency.
Develop methods to reconcile and connect disparate data points across systems to produce coherent, insight-ready datasets.
Cross-Functional Collaboration: Serve as a bridge between business teams and the Data Science & AI group, ensuring smooth data access and knowledge transfer.

Qualifications

3+ years of professional experience as a Data Analyst, BI Analyst, or in a similar analytical role.
Bachelor s degree in Data Science, Statistics, Computer Science, Business Analytics, or related field.
Strong SQL expertise for querying and transforming large datasets.
Proficiency in Python (Pandas, Polars, Dask, numpy, matplotlib/seaborn, Jupyter) for analysis and visualization.
Experience with Git and version control for managing analytical code and ensuring reproducibility.
Demonstrated ability to perform data cleaning, imputation/interpolation, and transformation at scale.
Hands-on experience with exploratory data analysis (EDA) and statistical techniques.
Experience integrating and connecting data from multiple sources to extract actionable insights.
Experience using BI/reporting tools with Tableau, Sigma (Or similar tools like Power BI).
Excellent communication and interviewing skills to engage with cross-functional teams and capture data knowledge effectively.
Strong organizational skills to build and maintain a living data inventory.
Understanding of AI/ML data workflows (feature engineering, model evaluation, monitoring) is a plus.
Familiarity with data governance practices and cloud environments (AWS, Snowflake, Azure, or GCP) is an asset.
Familiarity with feature stores for reusable AI/ML datasets is an asset.

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