Data Science Specialist

Tata Consultancy Services

Chennai District

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+

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Job summary

A leading IT consulting firm is seeking a Data Scientist to leverage data science for optimizing decision-making processes in operations. The role involves developing analytical models and algorithms, leading optimization solutions, and collaborating across teams. Ideal candidates should have 7-10 years of experience, strong skills in Python and machine learning, and a solid educational background in related fields. This is a full-time position with opportunities for professional growth.

Qualifications

5-10 years of experience in data science with proficiency in data mining.
Hands-on experience in predictive analytics and supply chain optimization.
Experience with machine learning frameworks and programming languages.

Responsibilities

Ensure decisions in the value chain are optimized through data science.
Build solutions for data-driven decision making to maximize ROI.
Design algorithms for vehicle routing and dynamic scheduling.

Skills

Data modeling

Python

Statistical analysis

Machine learning

SQL

Optimization techniques

Problem solving

Education

Bachelor’s or Master’s degree in operations research, Data Science

Tools

TensorFlow

PyTorch

Hadoop

Spark

Tableau

Power BI

Job description

Direct message the job poster from Tata Consultancy Services

Role: Data Scientist

Required Technical Skill Set: Hands-on experience in data modelling & optimization solutions along with functional expertise in operations domain.

Desired Experience Range: 8-12 Years

Location of Requirement: Bangalore/ Chennai/ Pune

Desired Competencies (Technical/Behavioral Competency)

Must-Have

Education: Bachelor’s or Master’s degree in operations research, Computer Science, Industrial Engineering, Data Science, or related field.
Experience: Minimum 7-10 years of experience in data science with leading industry or consulting services organizations with proficiency in data mining, mathematics, and statistical analysis.
Hands‑on experience in leading engagements in predictive analytics, supply chain modelling & optimization techniques to improve business performance and decision making through data‑driven solutions.
Sound understanding of logistics, transportation networks, and supply chain optimization solutions & algorithms development.
Strong analytical background with problem‑solving skills to contextualize complex business problems into implementable solutions given business constraints & limitations.
Ability to work effectively in a dynamic, research‑oriented group that has several concurrent projects.
Program / Project management experience in a fast‑paced environment with an ability to meet tight deadlines without compromising quality of deliverables.
Technical Skills:
Subject Matter expertise and sound knowledge & familiarity within Supply Chain concepts including Manufacturing, Warehousing, Inventory, Distribution & Logistics domain.
Deep analytical, technical, and complex problem‑solving skills set with expertise in mathematical optimization, statistical analysis, and advanced modeling techniques.
Proficiency in Python or R for data analysis and modelling.
Experience with machine learning frameworks, statistical analysis, and programming languages (e.g., TensorFlow, PyTorch, Scikit‑learn).
Strong knowledge of SQL and data manipulation.
Familiarity with big data tools (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, GCP).
Analytical Skills: Strong statistical knowledge, problem‑solving skills and ability to interpret complex datasets via critical thinking.

Good-to-Have

Experience with deep learning, NLP, or computer vision.
Knowledge of data visualization tools (Tableau, Power BI).
Business intuition and domain knowledge to understand business goals and frame the right questions with the client / internal stakeholders.
Background in deploying models in production environments.
Excellent soft skills, communication and presentation skills to explain complex ideas clearly to leadership level of audience.

Role descriptions / Expectations from the Role

1 Ensure every decision touch point of the value chain incl. Production, Inventory, Storage, Warehouse is defined in the most optimal manner leveraging data science in the given business context.

2 Build state-of-the-art solutions that facilitate data-driven decision making in specific business context to maximize ROI and automate the decision-making process via analytical dashboards.

3 Design and implement algorithms for Vehicle Routing Problems (VRP), scheduling, and dynamic routing under various industry environments to create the most efficient delivery routes, minimizing costs, time, and fuel and maximizing utilization.

4 Design, model and prototype machine learning models and algorithms to solve specific problems in the areas of Supply Chain, Warehousing & Logistics and deliver tangible value to the business, clearly articulated and measured by industry leading KPIs.

5 Ability to solve complex problems by deploying advanced optimization solutions in specific context related to multiple touchpoints of the supply chain, viz. transport routing, warehousing picking, packing operations, intra plant logistics using advanced MHEs like AGVs, AMRs, Robotics etc.

6 Bring thought leadership in developing proprietary & innovative solutions in niche and emerging areas in the industry landscape leveraged through data-science.

7 Work collaboratively across a range of stakeholders including DevOps, QA, Testing, Business, and cross-functional teams to develop & implement scalable solutions in live/production environment.

8 Apply techniques such as linear programming (LP), mixed-integer linear programming (MILP), and heuristics to analyze large datasets and integrate predictive models with optimization principles.

9 Develop and implement optimization models for vehicle routing, considering constraints like inventory, production, capacity, and other constraints to design most optimal transport routes.

11 Develop and implement machine learning models, statistical algorithms, and predictive analytics solutions.

12 Explore datasets to identify trends and insights, and use statistical analysis and hypothesis testing to understand complex issues.

13 Strong problem-solving skills and ability to clearly communicate insights and recommendations through clear visualizations and reports to drive data-driven decision making in the business.

14 Developing predictive models, performing statistical analysis, and creating data visualizations to communicate findings to stakeholders.

15 Stay updated with the latest advancements in data science, AI, and big data technologies and propose innovative solutions.

Seniority level