Data Scientist II

We're MiQ, a global programmatic media partner for marketers and agencies. Our people are at the heart of everything we do, so you will be too. No matter the role or the location, we're all united in the vision to lead the programmatic industry and make it better. As part of the Data Scientist team under DNA, you will assist in data analysis and interpretation to support business decision-making. Contribute to the development and implementation of data-driven solutions. Collaborate with cross-functional teams to gather insights and solve problems. Data preprocessing and cleaning. Assisting in developing and implementing predictive models. Supporting senior team members in data analysis tasks.

Responsibilities:

• Driving client stickiness: With your ability to leverage different datasets in the MiQ ecosystem, merge them together, and run the data science and machine learning models, you will assist the Sr. DS with data science product and solution development and deployment. Your capability to swiftly incorporate client feedback into the data science solutions will ensure that the client's stickiness is improved.
• Driving Profitability: By leveraging the power of data science and statistics, you are expected to work with other data scientists to identify areas where we can create data science-based activation or optimization solutions to optimize costs and enhance the performance of campaigns, thus making better margins and profitability in comparison to our competitors.
• MiQ Growth: Having a fair understanding of the data science products that are there in the outside market and the ability to leverage data in the MiQ ecosystem to re-create those solutions that can help support MiQ's business and tap into new revenue streams to drive growth.
• Support Key Decision-Making: Your knowledge of the data science and statistical analysis approach provides decision-makers with the necessary information to make informed choices. The data science-backed solutions help guide agencies, advertisers, and internal stakeholders in making strategic and tactical decisions that align with the MiQ's or client's objectives.
• Data Scientist Best Practices: As a Data Scientist II, you are expected to assist the initiative of introducing machine learning, data science, and statistics solution backend creation best practices within the team; help the team in the deployment of ML algorithms and solutions; and bring in quality frameworks within the team and to internal stakeholders.
• Developing Custom Analytics Solutions: Leveraging your knowledge of ML solution development, you will be expected to provide solutions to vertical-level problems and assist the development of MiQ local products in terms of DS expertise.
• Programmatic Traders: As a data scientist II, you collaborate with traders to test out the data science and ML-based activation solutions to help them optimize campaigns. By leveraging your modeling skills and understanding of the programmatic landscape, you provide actionable activation segments on audience targeting, ad performance, and bidding strategies. This helps traders make data-driven decisions, optimize their advertising campaigns, and improve overall campaign effectiveness and ROI.
• Product Managers: You work closely with the product managers to leverage the power of data partnerships, and through your DS model-building skills, you help uncover valuable insights about customer behavior, market trends, and campaign performance. This information allows product managers to create a product requirement and scoping document with all the necessary details about the product's USP and data science-related capabilities, thus outlining the course of product development.
• DNA Analysts, Consultants, and Data Scientists: You are required to work with the consultants, DNA analysts, and data scientists to form a team with all the expertise in place for robust product development. The product developed under local products will be a collaborative effort of all 3 experts. You will also have to assist in the effort of training all other DNA analysts on how to use a DS/ML-based solution, help them pitch to the client, and teach them how to measure the impact of the solution.

Requirements:

• Bachelor's or master's degree in computer science or mathematics/statistics.
• 2+ years of experience working on data science projects.
• Proficiency in programming languages such as Python/R.
• Experience in applying machine learning and statistical modeling (such as regression, classification, decision trees, forecasting, and clustering).
• Familiarity with data manipulation and visualization tools (e. g., pandas, matplotlib, seaborn).
• Familiarity with the end-to-end lifecycle of data science projects starting from conceptualization to deployment and monitoring.
• Hands-on experience in Pyspark and SQL for processing large datasets and extracting insights.
• A passion for keeping up with the latest technologies such as GenAI, deep neural networks, and Bayesian inference and applying them in relevant products.
• Effective communication skills for explaining technical concepts to non-technical stakeholders.