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Senior Data Scientist

nxzen(India)

Hyderabad, Telangana, India (Hybrid) · Full Time

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Experience
7+ yrs
Salary
Openings
1
Posted
10 hours ago
Work mode
Hybrid
Education
Any graduate
Eligibility
Any graduate is eligible to apply.
Resume
Required to apply

Where you'll work

Job description

About nxzen

nxzen Global is an innovative consulting, engineering, and operations organization specializing in the Energy and Utility sectors including Gas, Power, and Water. With a focus on delivering outcome-based turnkey solutions rooted in industry best practices and cutting-edge ideas, the company collaborates with clients across the value chain to drive sustainable efficiency and performance improvements. Their service portfolio includes strategy, consulting, digital transformation, technology, management, and operations services, with a strong emphasis on renewable energy development. They operate specialized business units and Centers of Excellence covering business operations, transformation, enterprise solutions, and network operations, executing projects like smart utility networks, technology optimization, asset management, and M&A advisory.

Role Overview

As a Senior Data Scientist at nxzen, based in Bangalore or Hyderabad with a hybrid working model, you will leverage your extensive experience in AI, machine learning, and predictive analytics to architect and deploy advanced AI solutions for enterprise clients. The position requires 7+ years of applied data science or machine learning expertise and involves leadership responsibilities, including guiding technical teams and collaborating globally.

Primary Responsibilities

  • Conceptualize and deploy predictive and machine learning models tailored to enterprise applications.
  • Develop statistical, optimization, and simulation models to facilitate informed business decision-making.
  • Conduct exploratory data analyses, feature engineering, and evaluate data quality.
  • Create and implement computer vision and natural language processing solutions where relevant.
  • Design and launch Generative AI applications utilizing Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and intelligent assistants.
  • Build and maintain MLOps and LLMOps pipelines to enable model deployment and monitoring.
  • Contribute to pre-sales activities, proof-of-concept developments, and AI solution innovation.
  • Lead and mentor small data science teams, fostering growth and technical excellence.
  • Collaborate with cross-regional teams to deliver enterprise-grade AI and analytics solutions.

Required Qualifications and Skills

  • Minimum 7 years professional experience in Data Science or Applied Machine Learning.
  • Proficient in Python programming, familiar with libraries such as Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, and deep learning frameworks like PyTorch or TensorFlow.
  • Expertise in predictive analytics, statistical modeling, time-series forecasting, and machine learning methodologies.
  • Hands-on experience with Generative AI technologies, including RAG, LLMs, prompt engineering, and vector databases.
  • Practical knowledge of cloud AI platforms like Azure ML, AWS SageMaker, Databricks ML, or Google Vertex AI.
  • Strong capabilities in SQL, Spark, data engineering concepts, and MLOps tools and practices.
  • Familiarity with containerization and orchestration tools such as Docker, Airflow, Kubeflow, MLflow, and continuous integration/deployment pipelines.
  • Excellent communication skills coupled with experience in stakeholder engagement and team leadership.

Benefits and Work Environment

  • Engage in enterprise-scale AI, machine learning, and data science initiatives.
  • Collaborate with global teams addressing real-world challenges in Energy and Critical Infrastructure sectors.
  • Exposure to innovative Generative AI and advanced analytics technologies.
  • Flexible hybrid work setup supporting excellent professional development and career progression.
  • Join a growing Data & AI practice known for delivering impactful, innovative solutions.

Work styles they’re looking for

Communication Leadership Collaboration Mentoring

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