We Love AI JobsData Scientist
GalentGalent is seeking a Data Scientist to develop intelligent data products and analytics solutions, focusing on generative AI applications and predictive modeling. This role offers the opportunity to collaborate with diverse teams in a dynamic environment, contributing to decision-making and operational optimization across various industries.
Skills & Expertise
Key Responsibilities
Develop predictive models and AI applications to support operational optimization.
Collaborate with cross-functional teams to translate business questions into data-driven insights.
Build and validate machine learning models for classification, regression, and clustering.
Full Description
Job Description:
We are looking for a Data Scientist with strong AI/ML capabilities and developer mindset to build intelligent data products and analytics solutions. The ideal candidate combines machine learning expertise with strong Python engineering skills and has an interest in GenAI applications and modern data platforms. This role will work closely with data engineering, product, and business teams to develop predictive models, AI applications, and data-driven insights that support decision-making and operational optimization. Data Scientist (AI/GenAI Developer) While not mandatory, experience working in industries such as Oil & Gas, Energy, Retail, or Marketing Analytics is considered an advantage.
Required Skills & Qualifications
* 4–8 years of experience in Data Science, Machine Learning, or AI-related roles.
* Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL.
* Experience building and validating machine learning models for classification, regression, clustering, or forecasting.
* Ability to work with large datasets and perform advanced feature engineering and model evaluation.
* Strong analytical thinking and ability to translate business questions into technical solutions.
* Excellent communication skills and ability to work in cross-functional teams.
To Have (Preferred)
* Experience with Generative AI / LLM frameworks (OpenAI, LangChain, HuggingFace, RAG architectures).
* Familiarity with cloud platforms and data platforms such as Azure, AWS, Databricks, or Snowflake.
* Experience with Spark or distributed data processing frameworks.
* Exposure to front-end technologies (Streamlit, Dash, React, or similar) for building analytics interfaces.
* Experience deploying models via APIs or building end-to-end AI applications.
* Domain exposure to Oil & Gas / Energy analytics, Retail analytics, or Marketing analytics.