Overview :
We are seeking a highly skilled and experienced Data Science professional to design, build, deploy, and optimize scalable data science solutions in complex environments. The ideal candidate brings strong technical expertise, deep theoretical understanding, and the ability to drive data-driven decision-making across the organization.
Key Responsibilities :
End-to-End Data Product Development :
- Design, prototype, productionize, and maintain robust, scalable, and high-performing data science products and machine learning pipelines.
Model Development & Deployment :
Build advanced statistical, machine learning, deep learning, and AI models, ensuring high accuracy, reliability, and business impact.System Design & Architecture :
Work closely with engineering and data teams to build scalable system architectures, pipelines, and production Data Analysis & Feature Engineering :Analyze structured and unstructured data, derive meaningful insights, and create high-value features for model development.Software Engineering & Code Quality :
Follow best practices in software development, version control, documentation, and modular code design.Data Processing & Pipelines :
Develop and manage automated, scalable data pipelines using modern tools and technologies.Cloud & Big Data Implementation :
Utilize cloud platforms (AWS, Azure, or GCP) and, where applicable, big data technologies like Hadoop, Spark, and Hive.Stakeholder Collaboration :
Work closely with product managers, engineering teams, senior leadership, and business stakeholders to gather requirements, present insights, and drive adoption of data Delivery :Maintain a pragmatic mindset by focusing on fast iteration, value delivery, and attention to detail while solving real-world business & Reporting :Prepare clear documentation, system specifications, performance reports, and technical Skills & Qualifications :7+ years of hands-on development experience in Python.Strong understanding of machine learning, deep learning, and the underlying mathematical principles.Advanced experience in SQL and performant database queries.Proficiency with Python frameworks and data science tools such as : NumPy, Pandas, PySpark, Matplotlib, Flask, FastAPI, scikit-learn, TensorFlow, PyTorch, etc.Strong background in :1. Data structures & algorithms
2. Software engineering practices
3. Data visualization and analytical tooling
Building and maintaining production-grade data pipelinesExperience with cloud environments : AWS, Azure, or GCP.Excellent problem-solving and analytical skills.Ability to lead teams and influence stakeholders without formal authority.Strong written and verbal communication skills.Preferred Qualifications (Nice to Have) :
Experience with big data platforms such as Hadoop, Hive, and Spark.Hands-on exposure to GenAI / LLM technologies, frameworks, or toolchains.Knowledge of experimental design, A / B testing, and statistical analysis.Experience in the energy industry is not required.(ref : hirist.tech)