About this Data Scientist role at Weekday AI
This role is for one of the Weekday's clients
Salary range: Rs 2000000 - Rs 6000000 (ie INR 20-60 LPA)
Experience: 4+ yrs
Location: Noida, Uttar Pradesh, India
Job Type: Full-Time
We are looking for an experienced Data Scientist who is passionate about transforming complex data into actionable business insights through advanced analytics, statistical modeling, and machine learning. This role is ideal for professionals who enjoy solving real-world problems using data, building predictive models, and influencing strategic product decisions through evidence-based recommendations.
As a Data Scientist, you will analyze large-scale datasets, develop predictive models, and design data-driven experiments that improve business outcomes and user experiences. You will collaborate closely with product, engineering, analytics, and business stakeholders to uncover meaningful insights, validate hypotheses, and build scalable machine learning solutions. This position requires a strong foundation in statistics, predictive analytics, data engineering concepts, and model deployment, along with the ability to communicate technical findings effectively to both technical and non-technical audiences.
Requirements
Key Responsibilities
- Develop predictive models to forecast business outcomes, user behavior, trends, and performance using statistical and machine learning techniques.
- Analyze large-scale structured and unstructured datasets to identify patterns, opportunities, and actionable insights.
- Design, execute, and evaluate A/B experiments using sound statistical methodologies and business-focused success metrics.
- Build end-to-end machine learning solutions, from exploratory data analysis and feature engineering to model development, validation, deployment, and monitoring.
- Perform data preprocessing, cleaning, transformation, and feature engineering to improve model accuracy and performance.
- Collaborate with engineering teams to develop scalable data pipelines and automate recurring machine learning workflows.
- Build dashboards, reports, and visualizations that clearly communicate analytical findings and business recommendations.
- Conduct model performance evaluation, validation, and continuous optimization using appropriate metrics and benchmarking techniques.
- Apply predictive analytics, statistical modeling, and causal analysis to support product improvements and strategic decision-making.
- Partner with cross-functional teams to translate business challenges into scalable data science solutions.
- Document methodologies, model assumptions, experimental results, and analytical insights to ensure transparency and reproducibility.
- Support deployment and monitoring of machine learning models within cloud-based or production data environments.
What Makes You a Great Fit
- Strong experience in Data Science, Machine Learning, and Predictive Analytics.
- Proficiency in Python, SQL, and widely used data science libraries such as NumPy, Pandas, Scikit-learn, and related tools.
- Solid understanding of statistics, hypothesis testing, regression, classification, clustering, and model evaluation techniques.
- Hands-on experience with data preprocessing, feature engineering, and end-to-end machine learning model development.
- Experience working with large datasets, data visualization platforms, and analytical reporting tools.
- Familiarity with cloud platforms, data pipelines, and production deployment of machine learning models is an advantage.
- Strong analytical thinking with the ability to solve complex business problems using data-driven approaches.
- Excellent communication skills with the ability to present technical insights to business stakeholders in a clear and actionable manner.
- Experience collaborating with cross-functional teams in Agile or fast-paced product environments.
- A proactive mindset, attention to detail, and passion for continuous learning in data science, artificial intelligence, and emerging analytics technologies.