Data Scientist

Societe Generale Global Solution Centre; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Societe Generale Global Solution Centre in Bengaluru is seeking a Data Scientist to design, develop and deploy robust machine learning solutions. You will leverage Python, ML, REST API and SQL to process complex data, build end-to-end models, and ensure data quality for analytics.

You will collaborate in Agile Scrum teams, document workflows, and work with multiple business domains to translate problems into data-driven solutions, including advanced NLP/LLM applications when applicable.

Qualifications

• Proficiency in Python, ML, REST API and SQL.
• Experience with data processing, cleansing and verification for analytics.
• Experience with data quality checks and exploratory analyses.
• Programming skills in Python and API development.
• Build end-to-end ML models with data transformation.
• Strong knowledge of statistical techniques and ML algorithms.
• Familiarity with data mining concepts and dashboards.

Responsibilities

• Leverage ML model experience to achieve business objectives in data environments.
• Inform model development and evaluation with mathematics and statistics background.
• Design, architect and develop robust ML solutions, integrating LLMs where applicable.
• Collaborate within Agile Scrum teams for iterative development.
• Document business processes, workflows, and requirements clearly.
• Collaborate with various domains to align with business needs.
• Participate in conceptualization sessions to refine project ideas.

Skills

Python

Machine Learning

REST API

SQL

Data processing

Data quality checks

Data visualization

Job description

• Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways.
• Utilize a solid background in mathematics and statistics to inform model development and evaluation.
• Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable.
• Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.
• Document business processes, workflows, and requirements clearly and comprehensively.
• Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs.
• Participate in collaborative conceptualization sessions to brainstorm and refine project ideas.

Reference 260009DZ

Responsibilities

• Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways.
• Utilize a solid background in mathematics and statistics to inform model development and evaluation.
• Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable.
• Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.
• Document business processes, workflows, and requirements clearly and comprehensively.
• Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs.
• Participate in collaborative conceptualization sessions to brainstorm and refine project ideas.

JD: Data Scientist

Responsibilities

• Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways.
• Utilize a solid background in mathematics and statistics to inform model development and evaluation.
• Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable.
• Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.
• Document business processes, workflows, and requirements clearly and comprehensively.
• Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs.
• Participate in collaborative conceptualization sessions to brainstorm and refine project ideas.

Mandatory Skills

• Proficiency in Python, Machine Learning, REST API, and SQL.
• Experience with data processing, cleansing, and verification to ensure data integrity for analysis.
• Conduct data quality checks and exploratory analyses to inform model development.
• Demonstrated programming skills in relevant languages, particularly Python and API development.
• Build end-to-end machine learning models, including data structures and transformation processes.
• Strong understanding of statistical modeling techniques (e.g., Regression, Clustering, Decision Trees, Logistic Regression).
• Familiarity with machine learning algorithms (e.g., KNN, Random Forests, Ensemble Methods, Bayesian/Markov Networks).
• Knowledge of data mining concepts and experience with data visualization tools and dashboards.

Preferred Skills

• Experience with Large Language Models (LLMs) such as GPT, BERT, or similar architectures.
• Understanding of natural language processing (NLP) techniques and their applications in business contexts.
• Familiarity with advanced research topics, including deep learning, kernel methods, spectral methods, and forecasting.
• Ability to integrate end-to-end ML solutions into product suites and business functions, with a focus on LLM applications.
• Design technical frameworks based on various use cases, particularly those involving text data and language understanding.
• Identify opportunities to automate analytical processes, data extraction, and flow processes, especially in the context of LLMs.
• Propose hypotheses and design experiments to address specific problems, leveraging LLM capabilities where relevant.

Additional Responsibilities

• Stay updated with the latest advancements in machine learning and natural language processing, particularly in the context of LLMs.
• Mentor junior team members on best practices in machine learning and LLM implementation.
• Contribute to the development of best practices and standards for machine learning and LLM projects within the organization.

Required

Profile required

• JD: Data Scientist

Responsibilities

• Leverage strong ML model experience in complex data environments to achieve business objectives in innovative and efficient ways.
• Utilize a solid background in mathematics and statistics to inform model development and evaluation.
• Design, architect, and develop robust machine learning solutions, with a focus on integrating Large Language Models (LLMs) where applicable.
• Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.
• Document business processes, workflows, and requirements clearly and comprehensively.
• Engage in close collaboration with various domains within the organization to ensure alignment and understanding of business needs.
• Participate in collaborative conceptualization sessions to brainstorm and refine project ideas.

Mandatory Skills

• Proficiency in Python, Machine Learning, REST API, and SQL.
• Experience with data processing, cleansing, and verification to ensure data integrity for analysis.
• Conduct data quality checks and exploratory analyses to inform model development.
• Demonstrated programming skills in relevant languages, particularly Python and API development.
• Build end-to-end machine learning models, including data structures and transformation processes.
• Strong understanding of statistical modeling techniques (e.g., Regression, Clustering, Decision Trees, Logistic Regression).
• Familiarity with machine learning algorithms (e.g., KNN, Random Forests, Ensemble Methods, Bayesian/Markov Networks).
• Knowledge of data mining concepts and experience with data visualization tools and dashboards.

Preferred Skills

• Experience with Large Language Models (LLMs) such as GPT, BERT, or similar architectures.
• Understanding of natural language processing (NLP) techniques and their applications in business contexts.
• Familiarity with advanced research topics, including deep learning, kernel methods, spectral methods, and forecasting.
• Ability to integrate end-to-end ML solutions into product suites and business functions, with a focus on LLM applications.
• Design technical frameworks based on various use cases, particularly those involving text data and language understanding.
• Identify opportunities to automate analytical processes, data extraction, and flow processes, especially in the context of LLMs.
• Propose hypotheses and design experiments to address specific problems, leveraging LLM capabilities where relevant.

Additional Responsibilities

• Stay updated with the latest advancements in machine learning and natural language processing, particularly in the context of LLMs.
• Mentor junior team members on best practices in machine learning and LLM implementation.
• Contribute to the development of best practices and standards for machine learning and LLM projects within the organization.

Why join us

We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Business insight

At Société Générale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether you’re joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us!

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