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Bhubaneswar, Odisha, India
Actively hiring, first seen by us todayWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Apply hypothesis testing, regression and time-series methods to large datasets
Review platform insights for sample size, significance, seasonality and bias
Investigate unusual results, find root causes, and fix or flag them
Design and analyze A/B tests and pilots to measure new features
Present findings to customers and internal stakeholders via reports and dashboards
Apply statistical methods such as hypothesis testing, regression, time-series analysis and probability modelling to large datasets.
Review the insights our platform produces for statistical soundness, including sample size, significance, seasonality and bias.
Investigate unusual results, identify root causes, and fix or flag them.
Design and analyze experiments (A/B tests, pilots) to measure the impact of new features.
Present findings to customers and internal stakeholders through reports, dashboards and walkthroughs.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 5 and day 41.
From 10,536 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
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LOCATION Bhubaneswar, Odisha EXPERIENCE 3–5 years EMPLOYMENT TYPE Full-time About the Role Our platform delivers data-driven insights to customers. We are looking for a statistically strong analyst to improve the quality of those insights and help customers get real value from them. You will work on large, real-world datasets, apply sound statistical methods to separate meaningful patterns from noise, and turn your findings into clear recommendations for customers and internal teams. The role suits someone who enjoys rigorous analysis and can explain results in simple terms. Requirements Key Responsibilities Statistical analysis and modelling • Apply statistical methods such as hypothesis testing, regression, time-series analysis and probability modelling to large datasets. • Design and improve methods for trend detection, anomaly and outlier detection, correlation analysis and forecasting. • Set confidence thresholds and validation checks so that only reliable insights reach customers. • Run exploratory data analysis to uncover new patterns and opportunities for insights. Insight quality and data integrity • Review the insights our platform produces for statistical soundness, including sample size, significance, seasonality and bias. • Investigate unusual results, identify root causes, and fix or flag them. • Build data quality checks and monitoring to catch problems early. Communicating insights • Present findings to customers and internal stakeholders through reports, dashboards and walkthroughs. • Translate business and customer questions into clear analytical problems and answer them with data. • Explain statistical concepts and their limitations in plain language to non-technical audiences. • Help Customer facing team with monthly metrics for internal customers and external customers Collaboration and improvement • Work with product and engineering teams to improve how insights are calculated and presented. • Design and analyze experiments (A/B tests, pilots) to measure the impact of new features. • Document methods and assumptions so analyses are consistent and repeatable. • Senior level: guide junior analysts and review their work for statistical accuracy. • Work closely with product management and customer facing teams to brainstorm on various analytics that will complement the product roadmap Required Qualifications • Bachelor’s or Master’s degree in Statistics, Mathematics, Applied Mathematics, Econometrics or a related quantitative field. • 3–5 years of hands-on experience in data analysis or statistical analysis. • Strong knowledge of applied statistics: hypothesis testing, confidence intervals, regression, time-series analysis, probability distributions and experimental design. • Strong SQL skills for querying and transforming large datasets. • Proficiency in Python or R (pandas, NumPy, SciPy, stats models, scikit-learn or equivalents). • Experience with at least one BI tool such as Power BI, Tableau, Looker or Meta base. • Ability to communicate findings clearly in writing and in presentations. Preferred Qualifications • Master’s degree in Statistics or Mathematics. • Experience with anomaly detection, forecasting or clustering techniques. • Experience with large-scale event, behavioral or time-series data. • Exposure to cloud data platforms (AWS, GCP or Azure) or big data tools such as Spark. • Experience in a client-facing analytics, consulting or SaaS product environment. Benefits What We Offer • Competitive salary and performance-linked bonus. • Health insurance for you and your family. • Learning budget for courses and certifications. • Real data problems that directly affect customers and the product.
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We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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Bhubaneswar, Odisha, India
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.