01Key Responsibilities
Translate business problems into well-defined analytical questions and structured
approaches
Support scenario, decision, and action modelling to evaluate business trade-offs and
inform recommended actions
Partner with Target business stakeholders to understand priorities and roadmaps,
validate analytical requirements, and present insights and recommendations with clarity
and impact
Develop and deliver analytical and AI-driven solutions (including GenAI, Agent, and
Agentic approaches) that enable decision support, forecasting, optimization, and
automation
Apply advanced analytics techniques, including causal, predictive, and prescriptive
analytics, to drive deeper understanding of business levers and inform optimal actions
Work with large-scale datasets using platforms such as GCP BigQuery, Spark, and SQL-
based data warehouses; build and maintain reliable data pipelines using Airflow or
similar orchestration tools
Contribute to AI-driven analytical workflows, defining quality metrics (e.g., accuracy,
relevance), assessing reliability, and measuring tangible business impact
Ensure analytical outputs are accurate, scalable, and aligned with business context
Develop strong data storytelling skills to communicate insights and recommendations to
non-technical audiences
Document analytical methodologies, assumptions, and outputs to support reuse and
knowledge sharing
Adhere to corporate data protection standards and responsible AI practices
Requirements / About You:
Experience: Overall 5-8 years exp and relevant 3-5 years exp
Qualification:
TI : B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent
US : BA/BS in a quantitative degree Math, Statistics, Econometrics, Data
Sciences, Computer Science or equivalent work experience
Skills required:
1. Extensive exposure to Structured Query Language (SQL), SQL Optimization and
DW/BI concepts.
2. Proven hands-on experience in BI Visualization tool (i.e. PBI, Looker, Tableau) with
ability to learn additional vendor and proprietary visualizations tools.
3. Strong knowledge of structured (i.e. Teradata, Oracle, Hive) and unstructured
databases including Hadoop Distributed File System (HDFS). Exposure and extensive
hands-on work with large data sets.
4. Hands on experience in R, Python, Hive or other open-source languages/database
5. Hands on experience in any advanced analytical techniques like Regression, Time-
series models, Classification Techniques, etc. and conceptual understanding of all
the techniques mentioned above
6. Git source code management & experience working in an agile environment.
7. Strong attention to detail, excellent diagnostic, and problem-solving skills
8. Highly self-motivated with a strong sense of urgency to be able to work both
independently and in team settings in a fast-paced environment; capability to
manage urgency timelines
9. Competent and curious to ask questions and learn to fill gaps, desire to teach and
learn.
10. Excellent communication, service orientation and strong relationship building skills
11. Experience with Retail, Merchandising, Marketing will be strong addons
12. Hands-on experience leveraging Generative AI (GenAI) and LLM-based solutions
(e.g., prompt engineering, Retrieval-Augmented Generation RAG) to enhance data
analysis, automate insight generation, and support business decision-making
13. Ability to integrate AI-driven tools and AI-agent workflows into end-to-end analytical
processes, enabling automation, improving productivity, and scaling analytics use
cases. .
