Decision Scientist Opportunity 2025 | Tesco is hiring Decision Scientist . The working location is Chennai, India. Interested candidates can apply online as soon as possible. The detailed eligibility and application process are given below.
Decision Scientist Opportunity at Tesco| Bengaluru – Overview
| Company Name: | Tesco |
| Job Role: | Decision Scientist |
| Location: | Chennai |
| Work Mode: | Hybrid |
| Last Date to Apply: | ASAP |
Job Description
- At Tesco, we are committed to providing the best for you. As a result, our colleagues enjoy a unique, differentiated, market- competitive reward package, based on the current industry practices, for all the work they put into serving our customers, communities and planet a little better every day. Our Tesco Rewards framework consists of pillars – Fixed Pay, Incentives, and Benefits. Total Rewards offered at Tesco is determined by four principles – simple, fair, competitive, and sustainable. Salary – Your fixed pay is the guaranteed pay as per your contract of employment. Performance Bonus – Opportunity to earn additional compensation bonus based on performance, paid annually Leave & Time-off – Colleagues are entitled to 30 days of leave (18 days of Earned Leave, 12 days of Casual/Sick Leave) and 10 national and festival holidays, as per the company’s policy. Making Retirement Tension-FreeSalary – In addition to Statutory retirement beneets, Tesco enables colleagues to participate in voluntary programmes like NPS and VPF. Health is Wealth – Tesco promotes programmes that support a culture of health and wellness including insurance for colleagues and their family. Our medical insurance provides coverage for dependents including parents or in-laws. Mental Wellbeing – We offer mental health support through self-help tools, community groups, ally networks, face-to-face counselling, and more for both colleagues and dependents
Skills Required:
- Identifying operational improvements and finding solutions by applying CI tools and techniques – Responsible for completing tasks and transactions within agreed KPI’s – Knows and applies fundamental work theories/concepts/processes in own areas of work Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making – In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources – Building Statistical models and ML algorithms with practitioner level competency – Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency – Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions – this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs – Working with the line manager to ensure application / consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any)
Responsibility:
- Identifying operational improvements and finding solutions by applying CI tools and techniques – Responsible for completing tasks and transactions within agreed KPI’s – Knows and applies fundamental work theories/concepts/processes in own areas of work Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making – In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources – Building Statistical models and ML algorithms with practitioner level competency – Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency – Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions – this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs – Working with the line manager to ensure application / consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any)
