Data Products Analyst (Healthcare, Consumer & Industrials)
Lattice Technologies Pvt Ltd · Gurgaon, Haryana, India
Business Consulting and Services · 51-200 employees
About the role
The Data Products Analyst will conduct industry research and collect, clean, and structure data to support the development of data-led products. They will also collaborate with product managers and technology teams to define data models, metrics, and automated processing workflows.
What they look for
Requirements
Candidates should have 2-5 years of experience in data analysis, market research, or consulting with proficiency in SQL and Excel. Strong analytical skills and the ability to structure unorganized information into actionable business insights are essential for this role.
Full description
About 1Lattice:
1Lattice™ is a 360-degree business decision support platform with a tech-enabled services stack of data, people network, and custom research. Powered by advanced tech tools and unique data-gathering approaches, 1Lattice offers an integrated product suite to make decisions smartly, right from Inputs to Validation, Execution and Measurement. 1Lattice works with clients and partners globally, helping them solve a wide variety of business and organizational problems through actionable research-led insights.
Role Overview
We are looking for a Data Products Analyst to support the development and delivery of data-led products across the Healthcare, Consumer and Industrials sectors.
The role involves understanding business requirements, conducting industry research, collecting and analysing data, and converting findings into structured datasets, insights and product features. The person will work closely with product managers, data teams and business stakeholders.
Key Responsibilities
- Conduct secondary research across Healthcare, Consumer and Industrials sectors.
- Understand business problems and convert them into clear data requirements.
- Collect, clean, validate and structure data from multiple public and internal sources.
- Analyse datasets to identify trends, patterns and actionable business insights.
- Help define data models, metrics, classifications and taxonomies for data products.
- Support the creation of dashboards, reports, market maps and analytical tools.
- Perform data quality checks and maintain accuracy and consistency across datasets.
- Work with technology teams to automate data collection and processing workflows.
- Use basic web scraping or data extraction techniques where required.
- Prepare clear documentation for data sources, methodologies and assumptions.
- Coordinate with product managers and business teams to deliver projects within agreed timelines.
Required Skills
- Strong analytical and problem-solving abilities.
- Good understanding of data collection, cleaning and analysis.
- Proficiency in Excel or Google Sheets.
- Working knowledge of SQL.
- Familiarity with Python, web scraping or data automation tools is preferred.
- Ability to structure unorganised information into usable datasets.
- Strong secondary research and business research skills.
- Ability to understand industry-specific terminology and business models.
- Good written and verbal communication skills.
- Strong attention to detail and ownership of data quality.
Qualifications and Experience
- The educational qualification is flexible; practical experience in data analysis, business research, market intelligence or data products will be given greater importance.
- 2–5 years of relevant work experience is preferred.
- Experience in Healthcare, Consumer, Industrials, market research, consulting or data-product roles will be an advantage.
- Exposure to BI tools such as Power BI, Tableau or Metabase is preferred.
- What We Are Looking For
- Someone who is curious about industries, companies and markets.
- Comfortable working with both business information and structured data.
- Able to independently research unfamiliar topics and develop a clear understanding.
- Capable of managing multiple workstreams while maintaining data accuracy.
- Interested in building reusable data products rather than only preparing one-time reports.
