Senior Consultant (Data Scientist), Value Engineering
New
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years
- Required Skills
- PythonSQLBusiness IntelligenceMicrosoft Power BITableauData scienceMicrosoft ExcelPowerPointR
Requirements
- Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, Economics, Engineering, Business, or a related discipline.
- 4+ years of experience in data science, analytics, business intelligence, or a related analytical role.
- Strong SQL skills and experience working with large-scale data environments and cloud-based data platforms.
- Experience developing dashboards and visualizations using tools such as Tableau, Power BI, or similar platforms.
- Advanced proficiency in Microsoft Excel and PowerPoint for analysis, reporting, and executive storytelling.
- Ability to analyze complex datasets and translate findings into actionable business recommendations.
- Strong communication and stakeholder management skills, with the ability to present insights to senior audiences.
- Experience with Python and/or R for analytics, automation, and modeling is preferred.
- Familiarity with AI automation tools, agentic AI solutions, or platforms such as Microsoft Copilot Studio is an advantage.
- Exposure to consulting, value engineering, ROI analysis, business case development, or client-facing analytics is preferred.
- Strong problem-solving skills, attention to detail, curiosity, and a continuous improvement mindset.
Responsibilities
- Develop and deliver reports, dashboards, and advanced analytical solutions using data from multiple internal and external sources.
- Analyze large datasets to identify trends, patterns, performance drivers, and opportunities for business improvement.
- Transform analytical findings into clear, compelling insights and recommendations for executive audiences and business leaders.
- Support the creation of executive presentations, value narratives, scorecards, and ROI measurement materials.
- Design and enhance value measurement frameworks to quantify business impact and track outcomes.
- Collaborate with analytics, product, consulting, and operational teams to develop data-driven strategies.
- Build reusable analytics assets, templates, and scalable workflows to improve efficiency and consistency.
- Leverage modern AI and automation tools, including agent-based solutions, to improve data retrieval, analysis, and insight generation.
- Contribute to client-facing analytics initiatives by connecting technical solutions with measurable business value.
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