HYDERABAD · FULLTIME
Data Scientist

Anblick Solutions
Hyderabad · onsite · Posted 1d ago
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Section · 01
About this role
POSITION OVERVIEW
DUTIES AND RESPONSIBILITIES Primary Responsibilities: Data Science and Measurement Analytics
- Support the design, development, testing, and validation of statistical and machine learning models for business measurement and analytical use cases.
- Perform exploratory data analysis (EDA), data preprocessing, feature engineering, and statistical analysis on large, complex datasets.
- Apply statistical modeling, hypothesis testing, experimental design, and causal inference techniques to identify patterns, measure outcomes, and generate actionable insights.
- Develop and evaluate models supporting incrementality and lift analysis, multi-touch attribution (MTA), marketing mix modeling (MMM), and rules-based attribution, where applicable.
- Analyze data from multiple sources, including customer interactions, media exposure, commerce, engagement, and business outcomes.
- Collaborate with Data Engineering teams to validate data quality, feature pipelines, data transformations, and model input datasets.
- Support the integration and validation of new data sources and partner feeds into analytical and modeling workflows.
- Evaluate model performance using appropriate statistical metrics, validation techniques, and performance benchmarks.
- Monitor deployed models and analytical workflows, identify data or performance issues, and recommend improvements.
- Document analytical methodologies, modeling assumptions, experiments, results, and reusable best practices.
- Translate business requirements into analytical problems and communicate findings, insights, and recommendations to technical and non-technical stakeholders.
- Support privacy-conscious analytical approaches that generate meaningful aggregate insights while protecting sensitive and individual-level data.
- Assist in developing scoring, segmentation, propensity, and predictive models using large-scale datasets.
- Explore identity-linked datasets and graph-based analytical approaches to understand relationships, patterns, and audience behavior.
- Contribute to analytical workflows involving secure data collaboration environments and data clean rooms, where applicable.
- Follow data privacy, security, governance, and responsible data handling practices throughout the model development lifecycle.
QUALIFICATIONS Required Qualifications
- Bachelors degree in Statistics, Computer Science, Data Science, Applied Mathematics, Economics, Engineering, or a related field.
- 3+ years of experience in Data Science, Applied Statistics, Machine Learning, or Analytics.
- Proficiency in Python or R and strong working knowledge of SQL for data extraction, transformation, and analysis.
- Understanding of statistical modeling, probability, hypothesis testing, regression analysis, and experimental design.
- Familiarity with causal inference concepts and the ability to interpret analytical results in a business context.
- Experience with exploratory data analysis, feature engineering, model development, and model validation.
- Ability to work with large, complex, multi-source datasets using cloud and data platforms such as Snowflake, Databricks, or AWS.
- Understanding of machine learning fundamentals, model evaluation techniques, and analytical best practices.
- Strong problem-solving, critical-thinking, and data interpretation skills.
- Excellent communication skills, with the ability to explain analytical findings and recommendations clearly.
- Exposure to marketing measurement methodologies, including incrementality testing, lift analysis, multi-touch attribution (MTA), marketing mix modeling (MMM), or rules-based attribution.
- Familiarity with marketing and media metrics such as impressions, reach, frequency, conversion rates, and attribution windows.
- Internship or professional experience in AdTech, MarTech, digital marketing analytics, customer analytics, or data-driven product environments.
- Exposure to identity resolution, graph-based data structures, identity-linked analytics, or privacy-preserving data clean rooms.
- Familiarity with data visualization and business intelligence tools such as Tableau, Looker, or Power BI.
- Experience working with external data sources, APIs, partner integrations, publishers, or retail media platforms.
- Coursework, certifications, or project experience in causal inference, A/B testing, experimentation, or statistical research.
- Familiarity with machine learning libraries such as scikit-learn, pandas, NumPy, and relevant statistical modeling packages.
- Exposure to LLMs, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and AI-assisted development tools such as GitHub Copilot or Claude Code.
- Understanding of best practices for validating AI-generated code, ensuring analytical accuracy, and using AI-assisted workflows responsibly.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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About Anblick Solutions

Anblick Solutions
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About
Anblicks, a team of specialists in strategic dUnlock the full potential of your data with Anblicks, a team of strategic data modernization experts. Our tailored services cover seamless data migration, robust re-architecture, and transformative solutions. The "AIM" Framework from Anblicks, encompassing Advise, Implement, and Manage, presents a dynamic methodology that simplifies data management. This approach effectively tailors, launches, and maintains data strategies. Anblicks guides its clients in customizing their data foundation, deploying an insight-driven platform, and provides continuous support with its innovative services. This empowers clients to fully leverage their data assets, securing their future capabilities. The framework promotes data democratization and governance, driving growth and enhancing competitive edges through strategic use of data and AI.
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