Te 1481 Data Analyst Hyderabad

Softobiz; Hyderabad; On-site; INR 700,000 - 1,200,000; Full time

Job summary

Softobiz is hiring a Data Analyst for a US healthcare business based in Hyderabad. You will analyze what data exists in BigQuery, determine what is worth monitoring, and build the dashboards that reveal actionable insights.

Expect to test hypotheses, distinguish correlation from causation, and present findings in plain language to leadership. You will work with the warehouse and engineering teams to pull data, create dashboards in Looker Studio, Power BI, or Tableau, and deliver continuous

Qualifications

• 3–6 years of data analytics experience.
• Experience with BigQuery and data warehouses.
• Ability to derive insights and recommendations from data.
• Experience with healthcare domain helpful.

Responsibilities

• Understand the data and map available sources.
• Explore data across BigQuery and other sources, assess reliability and gaps.
• Identify data genuinely helpful for business questions.
• Build dashboards that matter and monitor them after launch.
• Deliver ad hoc analysis for US leadership with quick turnaround.

Skills

SQL / BigQuery

Dashboard creation

Exploratory data analysis

Tools

Looker Studio

Power BI

Tableau

Job description

Data Analyst

Location: Hyderabad

Shift: US business hours overlap

Experience: 3 to 6 years

The role

We are hiring a Data Analyst for a US healthcare business. The data already lands in BigQuery and thepipelines are looked after by the engineering team. Your job starts after that: work out what data we actually have, what is worth paying attention to, and what it is telling us.This is an analysis and insight role with a data science lean. You will be expected to find your own wayaround the warehouse, pull and shape data yourself, build the dashboards that matter, and then gofurther than the dashboard. Why did a number move. Is it correlation or causation. What happens next.

Responsibilities

• Understanding the data


• Explore what data exists across BigQuery and other sources, and build a working view of what isavailable, how reliable it is, and where the gaps are


• Identify which data is genuinely helpful for the questions the business is asking


• Recommend what should be monitored on an ongoing basis, and why Pull and manipulate data in raw form without waiting on the engineering team

Analysis and insight

• Turn data into transparent observations and recommendations, not just charts


• Investigate why a metric moved: form a hypothesis, test it against the data, report the result in


• plain language


• Distinguish correlation from causation, and be explicit about which one you have


• Run cohort, segmentation, trend and outlier analysis across clinical, operational, member and growth data


• Deliver ad hoc analysis for US leadership on short turnaround

Dashboards and monitoring

• Build dashboards in Looker, Looker Studio, Power BI or Tableau covering the metrics that matter


• Own them after launch: monitor them, catch anomalies, breaks and trend changes before


• stakeholders do


• Retire or rebuild reporting that nobody uses or nobody trusts

Testing and predictive work

• Des .