Job Description
Purpose of the Position (Job Summary)
This role is ideal for someone with a strong product mindset and a proven ability to work independently, while mentoring a small team.
On site role at Jhagadia, Bharuch.
Key Individual Accountabilities
Data Science Solution Development
· Design and develop predictive and prescriptive models for manufacturing challenges such as process optimization, yield prediction, quality forecasting, downtime prevention, and energy usage minimization.
· Perform robust exploratory data analysis (EDA) and apply advanced statistical and machine learning techniques (supervised and unsupervised).
· Translate physical and chemical process knowledge into mathematical features or constraints in models.
· Deploy models into production environments (on-prem or cloud) with high robustness and monitoring.
Team Leadership & Management
· Lead a compact data science pod (2-3 members), assigning responsibilities, reviewing work, and mentoring junior data scientists or interns.
· Own the entire data science lifecycle: problem framing, model development, validation, deployment, monitoring, and retraining protocols.
Stakeholder Engagement & Collaboration
· Work directly with Process Engineers, Plant Operators, DCS system owners, and Business Heads to identify pain points and convert them into use-cases.
· Collaborate with Data Engineers and IT to ensure data pipelines and model interfaces are robust, secure, and scalable.
· Act as a translator between manufacturing business units and technical teams to ensure alignment and impact.
Solution Ownership & Documentation
· Independently manage and maintain use-cases through versioned model management, robust documentation, and logging.
· Define and monitor model KPIs (e.g., drift, accuracy, business impact) post-deployment and lead remediation efforts.
Key Interactions
Internals
-HODs
-Unit Management
-Team Members
Externals
-Vendors
Technical & Behavioral Skills & Knowledge
· 8+ years of experience in Data Science roles, with a strong portfolio of deployed use-cases in manufacturing, energy, or process industries.
· Proven track record of end-to-end model delivery (from data prep to business value realization).
· Master’s or Ph D in Data Science, Computer Science Engineering, Applied Mathematics, Chemical Engineering, Mechanical Engineering, or a related quantitative discipline.
· Expertise in Python (Pandas, Scikit-learn, Pyomo, XGBoost, etc.), and experience with cloud ML tooling (Azure ML, AWS Sagemaker, etc.).
· Familiarity with plant control systems (DCS, SCADA, OPC UA), historian databases (PI, Aspen IP.21), and time-series data.
· Experience in developing optimization models (LP, MILP, MINLP) for process or resource allocation problems is a strong plus.
Key Performance Indicators
· Familiarity with Gen AI/RAG frameworks for use-cases like documentation assistants or control room chatbots.
· Exposure to process simulation tools (Aspen Plus/HYSYS), sensor data fusion, or physics-informed ML.
· Experience working in Agile product development environments.
· Hands-on experience building dashboards (Power BI, Streamlit) for model visualization and interaction.
· Self-starter who thrives in low-data-maturity environments.
· Excellent problem-solving and analytical thinking tailored to real-world industrial constraints.
· Strong communication skills to explain complex technical outcomes to non-technical stakeholders.
· Ability to balance short-term delivery with long-term platform and model sustainability.
Competencies
Agile Towards Change and Innovation, PL1
Builds a Performance & Development Culture , PL1
Builds Partnership with Stakeholders, PL1
Executes Efficiently, PL1
Focused on Achieving Results, PL1
Thinks Strategically and Acts Decisively, PL1
What We Offer:
- A challenging and rewarding environment with significant opportunities for growth.
- Competitive salary and benefits.
How to Apply:
If you meet the qualifications and experience needed for this position, please click the "Apply" button to submit your application, and also follow our page for further updates.
This role is ideal for someone with a strong product mindset and a proven ability to work independently, while mentoring a small team.
On site role at Jhagadia, Bharuch.
Key Individual Accountabilities
Data Science Solution Development
· Design and develop predictive and prescriptive models for manufacturing challenges such as process optimization, yield prediction, quality forecasting, downtime prevention, and energy usage minimization.
· Perform robust exploratory data analysis (EDA) and apply advanced statistical and machine learning techniques (supervised and unsupervised).
· Translate physical and chemical process knowledge into mathematical features or constraints in models.
· Deploy models into production environments (on-prem or cloud) with high robustness and monitoring.
Team Leadership & Management
· Lead a compact data science pod (2-3 members), assigning responsibilities, reviewing work, and mentoring junior data scientists or interns.
· Own the entire data science lifecycle: problem framing, model development, validation, deployment, monitoring, and retraining protocols.
Stakeholder Engagement & Collaboration
· Work directly with Process Engineers, Plant Operators, DCS system owners, and Business Heads to identify pain points and convert them into use-cases.
· Collaborate with Data Engineers and IT to ensure data pipelines and model interfaces are robust, secure, and scalable.
· Act as a translator between manufacturing business units and technical teams to ensure alignment and impact.
Solution Ownership & Documentation
· Independently manage and maintain use-cases through versioned model management, robust documentation, and logging.
· Define and monitor model KPIs (e.g., drift, accuracy, business impact) post-deployment and lead remediation efforts.
Key Interactions
Internals
-HODs
-Unit Management
-Team Members
Externals
-Vendors
Technical & Behavioral Skills & Knowledge
· 8+ years of experience in Data Science roles, with a strong portfolio of deployed use-cases in manufacturing, energy, or process industries.
· Proven track record of end-to-end model delivery (from data prep to business value realization).
· Master’s or Ph D in Data Science, Computer Science Engineering, Applied Mathematics, Chemical Engineering, Mechanical Engineering, or a related quantitative discipline.
· Expertise in Python (Pandas, Scikit-learn, Pyomo, XGBoost, etc.), and experience with cloud ML tooling (Azure ML, AWS Sagemaker, etc.).
· Familiarity with plant control systems (DCS, SCADA, OPC UA), historian databases (PI, Aspen IP.21), and time-series data.
· Experience in developing optimization models (LP, MILP, MINLP) for process or resource allocation problems is a strong plus.
Key Performance Indicators
· Familiarity with Gen AI/RAG frameworks for use-cases like documentation assistants or control room chatbots.
· Exposure to process simulation tools (Aspen Plus/HYSYS), sensor data fusion, or physics-informed ML.
· Experience working in Agile product development environments.
· Hands-on experience building dashboards (Power BI, Streamlit) for model visualization and interaction.
· Self-starter who thrives in low-data-maturity environments.
· Excellent problem-solving and analytical thinking tailored to real-world industrial constraints.
· Strong communication skills to explain complex technical outcomes to non-technical stakeholders.
· Ability to balance short-term delivery with long-term platform and model sustainability.
Competencies
Agile Towards Change and Innovation, PL1
Builds a Performance & Development Culture , PL1
Builds Partnership with Stakeholders, PL1
Executes Efficiently, PL1
Focused on Achieving Results, PL1
Thinks Strategically and Acts Decisively, PL1
What We Offer:
- A challenging and rewarding environment with significant opportunities for growth.
- Competitive salary and benefits.
How to Apply:
If you meet the qualifications and experience needed for this position, please click the "Apply" button to submit your application, and also follow our page for further updates.
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