Data Science Manager

Tredence; Bengaluru; Hybrid; INR 2,000,000 - 2,500,000; Full time

Job summary

Tredence is seeking a Lead Senior Data Scientist to drive advanced analytics and machine learning initiatives in Bengaluru. The role involves leading model development for demand prediction and optimization while collaborating with various teams to embed data-driven insights into decision-making.

The ideal candidate should have 8-11 years of experience in data science, strong skills in Python and SQL, and expertise in time series forecasting. A Master's or PhD in a relevant field is preferred.

Qualifications

• 8-11 years of experience in Data Science, with demonstrable business impact.
• Strong programming expertise in Python.
• Deep knowledge of machine learning algorithms and forecasting techniques.

Responsibilities

• Lead the design and deployment of advanced ML models.
• Collaborate with stakeholders to embed models into systems.
• Mentor junior data scientists.

Skills

Python expertise (pandas, scikit‑learn, statsmodels, PyTorch/TensorFlow)

Advanced SQL proficiency

Machine learning algorithms knowledge

Time series forecasting expertise

Experience with distributed computing tools

Data visualization tools familiarity

Leadership skills

Education

Master's or PhD in a relevant field

Tools

Spark

Hadoop

AWS

Azure

GCP

Job description

Lead Senior Data Scientist (L4)

We are seeking a highly experienced Lead Senior Data Scientist to drive advanced analytics and machine learning initiatives across critical business domains. The ideal candidate will bring deep expertise in time series forecasting, machine learning, and optimization techniques, along with proven leadership in guiding teams and delivering measurable business impact.

Key Responsibilities

• Lead the design, development, and deployment of advanced ML and forecasting models for demand prediction, dynamic pricing, and inventory optimization.
• Translate complex business challenges into scalable analytical frameworks and actionable strategies.
• Architect and oversee end‑to‑end data science workflows, including data pipelines, model training, validation, and production deployment.
• Collaborate with engineering, product, and business stakeholders to embed models into decision‑making systems.
• Drive innovation by evaluating emerging ML techniques (transformers, deep learning, ensemble methods) and applying them to real‑world problems.
• Mentor and guide junior and mid‑level data scientists, fostering a culture of technical excellence and continuous learning.
• Present insights and recommendations to senior leadership using compelling data visualizations and storytelling.
• Ensure best practices in MLOps, reproducibility, and scalable deployment of models.

Required Skills and Experience

• 8‑11 years of experience in Data Science, Machine Learning, or Advanced Analytics roles with demonstrable business impact.
• Strong programming expertise in Python (pandas, scikit‑learn, statsmodels, PyTorch/TensorFlow).
• Advanced proficiency in SQL for large‑scale data manipulation.
• Deep knowledge of machine learning algorithms (regression, classification, clustering, ensemble methods, gradient boosting, decision trees).
• Proven expertise in time series forecasting (ARIMA, Prophet, LSTM, transformer‑based forecasting models).
• Experience in one or more domains:
  • Demand Forecasting
  • Price Optimization
  • Inventory Optimization / Supply Chain Analytics
• Hands‑on experience with distributed computing tools (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Strong quantitative, problem‑solving, and leadership skills.
• Familiarity with data visualization tools (Tableau, Power BI, matplotlib, seaborn).

Preferred Qualifications

• Master's or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or related fields.
• Industry experience in retail, e‑commerce, manufacturing, or logistics.
• Exposure to optimization libraries (PuLP, OR‑Tools, Gurobi) and advanced operations research techniques.
• Experience with MLOps platforms (MLflow, Kubeflow, SageMaker) for scalable deployment.
• Track record of leading cross‑functional projects and delivering enterprise‑level solutions.