Job Title

Position Title Senior Data Scientist 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 Internal 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 PhD 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 GenAI/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 (PowerBI, 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, PL1Builds a Performance & Development Culture , PL1Builds Partnership with Stakeholders, PL1Executes Efficiently , PL1Focused on Achieving Results, PL1Thinks Strategically and Acts Decisively, PL1