Data Scientist - Machine Learning / Predictive Analytics

What Youll Do :

As a Data Scientist Analytics, you will leverage your expertise in machine learning and statistics to solve complex, high-impact business problems in the areas of demand planning, forecasting, and anomaly detection.

You'll work collaboratively with cross-functional teams to develop, fine-tune, and implement AI / ML-driven solutions for clients, focusing on delivering measurable value and actionable Responsibilities :

Apply state-of-the-art AI / ML techniques to solve business challenges such as :

a. Demand sensing & forecasting

b. Outlier detection & history correction

c. Anomaly detection

d. Pricing optimization

• Explainable AI (XAI) for model transparency
• Develop and fine-tune statistical and machine learning models to handle time series forecasting use-cases
• Analyze large, complex datasets to identify trends and insights and determine the best modeling approaches
• Apply and track business-relevant metrics like Forecast Accuracy, Bias, and MAPE, and define new KPIs as needed
• Present analytical findings and model results in a clear, insightful manner to clients and internal stakeholders
• Collaborate with Project Managers, Solution Architects, Data Engineers, Consultants, and Product Teams to ensure successful model integration and project delivery
• Rapidly prototype, test, and iterate models with a focus on scalability and Youll Have :
• 4+ years of total experience in Data Science
• Minimum 2 years of experience in commercial or enterprise projects involving time series forecasting, demand planning, or predictive analytics
• Hands-on experience with statistical modeling, machine learning, and feature engineering
• Proven ability to work independently to extract insights from messy, real-world data and define the right modeling strategy
• Strong experience in data quality assessment, data transformation, and working with imperfect data
• Ability to clearly communicate complex technical concepts to non-technical stakeholders
• Exposure to Agile methodologies and fast-paced environments requiring rapid experimentation and iteration
• Masters degree in Computer Science, Statistics, Economics, Mathematics, Engineering, or a related quantitative Skills :

Programming & Tools : Python, PySpark, SQL

Libraries : Scikit-learn, XGBoost, Prophet, TensorFlow / Keras & BI : Tableau, Power BI (for model integration and building models in a cloud or distributed computing environment is a strong plus

ref : hirist.tech)