Job Overview
Role: AI/ML Data Scientist I Location: Bengaluru Experience: 0–3 Years Qualification: relevant degree in data science, statistics, engineering, mathematics, operations research, information sciences, or related scientific disciplines Key Skills: Python, Spark, AWS, SQL, Artificial Intelligence, Machine Learning
Job Description
Nielsen is seeking an AI/ML Data Scientist I in Bengaluru for early-career professionals with 0-3 years of experience and a relevant degree. This hybrid role focuses on Artificial Intelligence, Machine Learning, Data Science, and large-scale data analytics, specifically within real-world machine learning, data engineering, statistical methodology, cloud computing, and audience measurement problems. The position spans the entire data science project lifecycle, from data exploration and cleaning to applying advanced techniques, building and deploying production-ready data pipelines and machine learning models, and documenting methodologies. Candidates will contribute to measurement and planning solutions for publishers, advertisers, and agencies, addressing complex audience measurement challenges like trend analysis, missing-data imputation, and data integration.
Roles and Responsibilities
- AI/ML Solution Development: Build measurement and planning solutions; Identify opportunities where Artificial Intelligence can improve projects; Implement AI-based solutions; Support reproducible data science projects end-to-end; Develop and maintain production data pipelines; Deploy and maintain machine learning models in production environments; Work with cross-functional teams to productionize analytical methodologies; Validate and optimize data science methodologies and models; Document new methodologies, analytical approaches, and code.
- Data Analysis & Research: Support research related to cross-platform audience measurement; Perform trend analysis and investigate patterns within large datasets; Work with missing-data imputation and representation techniques; Support sampling and bias-reduction methodologies; Work on indirect estimation and data integration problems; Explore datasets to identify relevant variables and relationships; Clean and prepare large datasets for analysis; Apply dimension reduction techniques; Calculate distances and integrate survey data; Evaluate analytical outputs to ensure accuracy and reliability; Investigate quality escapes and fix issues in production code.
- Communication: Communicate methodology and research findings to technical and non-technical audiences.
Skills and Eligibility Criteria
Educational Background: relevant degree in data science, statistics, engineering, mathematics, operations research, information sciences, or related scientific disciplines
Experience: 0–3 years of professional experience.
Mandatory Technical Skills:
- Proficiency in Python.
- Knowledge of Apache Spark.
- Familiarity with AWS and cloud computing.
- Proficiency in SQL.
- Knowledge of Artificial Intelligence and Machine Learning concepts.
- Understanding of statistical concepts and analytical methodologies.
- Ability to manipulate, analyze, and interpret large datasets.
- Experience with Git and GitLab or similar version-control systems.
- Familiarity with dashboarding and visualization tools such as Spotfire or Tableau.
- Familiarity with JIRA and Confluence.
Competencies:
- Strong ability to document code and analytical methodologies.
- Strong written and verbal communication skills.
- Ability to work effectively with distributed and cross-functional teams.