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Data Scientist

Gevernova
  • 🇮🇳 India
  • On-site
  • 1 day ago
  • Machine Learning
  • Python
  • SQL
  • Pandas
  • NumPy
  • scikit-learn
  • TensorFlow
  • PyTorch
  • ETL
  • AWS SageMaker
  • Azure ML
  • GCP
  • Vertex AI
  • MLOps
1 day ago
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Job Description Summary

The Data Scientist executes end-to-end Data Science and Machine Learning workflows under guidance to deliver measurable value in industrial operations. You will focus on data acquisition/cleaning, feature engineering, exploratory analysis, model development/validation, and contribute to deployment and monitoring in collaboration with data/platform engineering. Primary use cases include time-series forecasting, anomaly detection, and predictive maintenance, with Generative AI (GenAI) as an added advantage. Exposure to operations in Oil & Gas, Fossil Power, or Renewable Power is a plus.

Job Description

Roles and Responsibilities

  • Execute DS/ML tasks across the model lifecycle: data acquisition, quality assessment/cleansing, feature engineering, and exploratory data analysis on industrial datasets (sensor/telemetry, logs, emissions, maintenance) with reproducible workflows.
  • Train, tune, and validate models (regression, classification, and time-series methods such as ARIMA/Prophet; anomaly detection; ensembles). Document experiments and results clearly.
  • Collaborate with data/platform engineering to contribute to data pipelines and model serving; support deployment activities and basic monitoring/drift checks under supervision.
  • Produce clean, well-structured Python/SQL code; follow coding standards, version control, and experiment tracking practices.
  • Create visual analyses and concise summaries to communicate findings and recommendations to teammates and stakeholders; incorporate feedback to iterate.
  • Assist in measuring outcomes against success metrics (e.g., reliability, availability, efficiency, emissions, cost) and maintain project artifacts (reports, annotated code).
  • Learn industrial context, data sources, and domain constraints; proactively identify data quality issues and propose fixes within established procedures.
  • Participate in POCs/pilots, including GenAI/LLM-assisted analytics workflows (analytics automation, documentation) as an added advantage.

Education Qualification: Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum 3 years of experience in Data Science/Machine Learning or closely related roles.


Desired Characteristics

Technical Expertise:

  • Proficient in Python and SQL; hands-on with Pandas, NumPy, scikit-learn; basic exposure to TensorFlow/PyTorch is a plus.
  • Applied experience with feature engineering, model selection, cross-validation, and performance measurement for time-series and classification/regression problems.
  • Solid foundations in data management: ETL basics, data quality checks/cleansing, and working with large datasets.
  • Familiarity with cloud ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI) and MLOps concepts (experiment tracking, model registry, monitoring) is a plus.
  • Competent in visual analytics for EDA and communicating insights; experience with dashboards or notebooks preferred.
  • Familiarity with big data/streaming technologies (e.g., Spark, Kafka) and real-time analytics considerations is a plus.

Domain Knowledge:

  • Exposure to industrial operations (Oil & Gas, Fossil Power, Renewable Power) is a plus; ability to learn failure modes, maintenance strategies, and process constraints and translate them into features and validation criteria.
  • Basic understanding of business drivers and operational KPIs (availability, MTBF/MTTR, throughput, energy yield, emissions, cost) with the ability to connect analytical results to business value.

Personal Attributes:

  • Curiosity and continuous learning mindset; connects ideas and incorporates feedback quickly.
  • Comfort in ambiguity at project/task level; states assumptions clearly and adapts based on new information.
  • Clear communicator; explains technical information to teammates and stakeholders and asks clarifying questions to ensure shared understanding.


Additional Information

Relocation Assistance Provided:Yes

 

 

Data Scientist · Gevernova

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