Description :

What Youll Do :

We are looking for a passionate and highly analytical Data Scientist to join our growing team and help shape the future of our data-driven product strategies. In this role, you will:

Strategic Data Leadership :

- Partner closely with Product, Engineering, Growth, Operations, and Business Intelligence teams to identify opportunities where data can deliver tangible impact on user experience and business outcomes.

- Translate ambiguous business problems into well-defined analytical challenges and robust data science solutions.

Machine Learning & Modeling :

- Design, build, validate, and iterate on machine learning models that power key product capabilities such as recommendation engines, user profiling, customer segmentation, personalization, anomaly detection, and NLP/text analytics.

- Conduct rigorous model evaluation, error analysis, and performance optimization to ensure models perform reliably at scale in real-world production environments.

Advanced Analytics & Insight Generation :

- Analyze complex, large-scale structured and unstructured data to uncover patterns, trends, and opportunities that inform product decisions and strategic direction.

- Use statistical inference, experiment design (e.g., A/B testing), and causal analysis to validate hypotheses and guide product optimizations.

Data Engineering & Collaboration :

- Work with Data Engineering teams to ensure high-quality data pipelines, ETL/ELT processes, and scalable data infrastructure.

- Collaborate with Software Engineers and MLOps teams to deploy and monitor models in production, ensuring reliability, performance tracking, and retraining schedules.

Communication & Visualization :

- Translate complex analytical results into clear, compelling narratives and visualizations for technical and non-technical stakeholders using tools like Tableau, Looker, Redshift, or similar.

- Present findings, insights, and recommendations in meetings, reports, and strategic reviews.

What Were Looking For :

Core Qualifications :

- 3 to 5 years of industry experience in data science, analytics, or machine learning preferably with consumer internet or high-growth B2C products.

- Bachelors or Masters degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field (or equivalent hands-on experience/certification).

Technical Expertise :

- Machine Learning & AI: Proven experience with building and deploying models such as collaborative filtering, clustering, classification, regression, NLP/text classification, embeddings, and anomaly detection.

- Statistics & Data Analysis: Deep understanding of statistical methods, experiment design, hypothesis testing, and data sampling techniques to drive meaningful insights from large datasets.

- Programming & Tools: Expert in Python or R, strong SQL skills, and practical use of libraries and frameworks like NumPy, Pandas, scikit-learn, Keras, TensorFlow/PyTorch or similar tools.

- Data Wrangling & Visualization: Experience preparing, cleaning, and exploring datasets with tools including Redshift, Tableau, Looker, or equivalent BI/visualization platforms.

Soft Skills :

- A curious problem-solver with an analytical mindset and the ability to approach complex questions from first principles.

- Excellent communication skills with the ability to present complex ideas simply and persuasively.

- Self-starter who thrives in a fast-paced environment and balances multiple priorities independently.

Good To Have (Nice-to-Haves) :

- Experience with big data platforms such as Hadoop, Spark, Hive, Pig, or distributed computing environments.

- Familiarity with cloud services (AWS, GCP, Azure) and orchestration tools (Airflow, dbt).

- Prior exposure to production-level model deployment, MLOps frameworks, or automated retraining pipelines.

- Experience with A/B testing, causal inference frameworks, or experimentation platforms.