Description

JD for Data Scientist

Responsibilities

As a Data Scientist, you will:

Core Delivery

- Work as part of a cross disciplinary squad, closely collaborating with data scientists, data engineers, software engineers, product managers, and commercial stakeholders.
- Design, build, and productionise scalable data science solutions – including statistical models, optimisation frameworks, and machine learning algorithms and pipelines – that support pricing decisions and testing.
- Carry out data analyses to yield actionable business insights.
- Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation).
- Conduct exploratory and statistical analyses of large, complex datasets to uncover pricing insights, elasticity patterns, customer behaviour trends, and commercial opportunities.
- Design, implement, and evaluate price experiments (e.g. A/B tests, quasi experiments) in partnership with commercial teams.
- Contribute to the design and monitoring of machine learning systems deployed in production, including alerting, logging, testing, and technical documentation.
- Present results to peers and senior management.
- Actively contribute to improve developer velocity.

[hr align="center" size="2" width="100%"] Qualifications

Essential

- Qualification in a quantitative discipline (e.g. statistics, mathematics, econometrics, computer science, physics, engineering).
- Typically 5+ years of hands on experience designing, building, deploying, and maintaining robust data science or machine-learning systems in production environments.
- Robust theoretical grounding in statistics and machine learning, including:
- regression / classification methods




- causal inference and experimental design
- optimisation and time‑series modelling

- Strong Python coding skills, including the ability to write robust, understandable, test driven code.
- Advanced SQL skills.
- Experience working with cloud scale datasets and modern data engineering / MLOps workflows.
- Ability to translate ambiguous business problems into analytical approaches, and to communicate complex findings clearly.
- Customer centric, pragmatic mindset with focus on value delivery and iterative execution.
- Strong stakeholder management and ability to influence without direct authority.

Desired

- Experience with distributed data processing (e.g. Spark, Hive, Hadoop) is a plus.
- Exposure to or interest in price optimisation, revenue management, commercial strategy, or experimentation at scale (prior price optimisation experience not a strict requirement).
- No prior experience in the energy sector is necessary.
- Familiarity with deploying ML models into production and monitoring their performance over time.

Enable Skills-Based Hiring No ECMS REQ IDAdditional Details

- ECMS REQ ID : 584207
- Project Location 1 : Pan India
- Project Location 2 : (No Value)
- Project Location 3 : (No Value)
- Project Location 4 : (No Value)
- Delivery SPOC : Nishit Kumar
- Relevant Experience : 6+ years
- Mandatory skills : • Qualification in a quantitative discipline (e.g. statistics, mathematics, econometrics,



computer science, physics, engineering).• Typically 5+ years of hands on experience designing, building, deploying, and maintaining robust data science or machine-learning systems in production environments. • Robust theoretical grounding in statistics and machine learning, including: o regression / classification methodso causal inference and experimental designo optimisation and time series modelling• Strong Python coding skills, including the ability to write robust, understandable, test driven code.• Advanced SQL skills.• Experience working with cloud scale datasets and modern data engineering / MLOps workflows.• Ability to translate ambiguous business problems into analytical approaches, and to communicate complex findings clearly.• Customer centric, pragmatic mindset with focus on value delivery and iterative execution.• Strong stakeholder management and ability to influence without direct authority.
- Desired skills : • Experience with distributed data processing (e.g. Spark, Hive, Hadoop) is a plus.• Exposure to or interest in price optimisation, revenue management, commercial strategy, or experimentation at scale (prior price optimisation experience not a strict requirement).• No prior experience in the energy sector is necessary.• Familiarity with deploying ML models into production and monitoring their performance over time.
- Domain (Industry) : Oil & Gas
- BGC (Before onboarding / After onboarding) : PostOB
- Total Experience (Ex. 5-7 Years) : 6+ Years
- BGC Details : Infosys Standard Checklist
- BGC Vendor : Any NASSCOM Vendor
- Mode of Interview : Face to Face
- WFO / WFH / Hybrid : Hybrid
- Please enter shift timings : UK Shift
- Shift Timings : Afternoon

📌 584207 | Data Scientist | IC | Pan India (Bengaluru)
🏢 Trigent Software
📍 Bengaluru