Data Scientist

Data Scientist

We are seeking a Data Scientist with around 3 years of experience to join our analytics and machine learning team in the Ad Tech domain. In this role, you will apply statistical and machine learning techniques to improve campaign targeting, audience segmentation, and recommendation systems. You will collaborate with engineers, analysts, and product teams to transform data into insights and deploy models that directly impact business outcomes. This position is ideal for someone eager to take ownership of end-to-end projects while continuing to expand their expertise in advanced machine learning and applied statistics.

Key Responsibilities

• Develop and deploy machine learning and statistical models to solve business problems in advertising and marketing.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and actionable insights.
• Design and run experiments (e.g., A/B testing) to evaluate impact and validate hypotheses.
• Work with engineers to build and maintain scalable data pipelines that support modeling and analytics.
• Communicate results effectively through dashboards, visualizations, and presentations .
• Stay up to date with new techniques in machine learning, causal inference, and recommendation systems and apply them where relevant.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Physics).
• ~3 years of experience applying machine learning and statistical methods in a professional setting.
• Strong proficiency in Python or R and SQL .
• Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch .
• Hands-on knowledge in at least one of the following: A/B testing, causal inference, NLP, or recommendation systems .
• Strong problem-solving, analytical, and communication skills.

Nice-to-Have

• Prior experience in Ad Tech, digital marketing, or related industries .
• Familiarity with big data and distributed systems (e.g., Spark, Databricks, GCP).
• Experience with time series forecasting or advanced NLP techniques .