Expert - Process Automation - Vdc - Chennai, Tamil Nadu, India - DHL

DHL

Verified Company

Chennai, Tamil Nadu, India

2 weeks ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

Join our "Digital Service Lab" at DHL Global Forwarding, Freight (DGFF) GSC - Global Service Centre

Job Title:
Expert, Data Scientist - Digital Service Lab, GSC MAA

Job Location:
India - Chennai

Business Area:
GSC, DGFF

Department:

DSL

Grade:
L

Are you dynamic and results-oriented with a passion for logistics? Join our high-performing Global Shared Services Team (GSC) at DHL Global Forwarding, Freight (DGFF); a Great Place to Work certified organization and one of the "Top 20 most admired Shared Services Organizations in 2022" by the independent global Shared Services & Outsourcing Network (SSON).

We are the captive Shared Service Provider for DHL Global Forwarding and DHL Freight (DGFF).

We are an organization of more than 4,600 colleagues complemented by approximately 500 virtual FTE (i.e., bots applied in process automation).

Our colleagues are based across six service delivery centers in Mumbai, Chennai, Chengdu, Manila, Bogota & Budapest. You will interact with people from all over the world and get the chance to a truly international organization.

As an Expert Data Scientist at
DSL, the role will lead data analysis and modelling initiatives, collaborating with cross-functional teams to derive actionable insights and drive decision-making processes.

With advanced expertise in machine learning and statistical analysis, the role will be key in translating complex data into strategic recommendations to support
DSL's objectives and foster innovation.

Key Responsibilities:

-
Collaboration and Requirement Gathering:

Collaborate closely with business partners and Global Service Center (GSC) stakeholders to understand their objectives, challenges, and data requirements.
Translate business objectives into actionable data science projects, ensuring alignment with organizational goals and priorities.

-
Data Preprocessing and Analysis:

Clean, preprocess, and analyse large datasets to extract meaningful insights, identify trends, patterns, and correlations relevant to business objectives.
Utilize advanced data manipulation techniques to ensure data quality and integrity before analysis.

-
Model Development and Optimization:

Develop predictive models and machine learning algorithms to address business problems and optimize processes, leveraging techniques such as regression, classification, and clustering.
Continuously evaluate model performance, conduct A/B testing, and iterate on models to improve accuracy, efficiency, and business impact.

-
Communication and Stakeholder Engagement:

Effectively communicate findings and insights derived from data analysis and modeling to nontechnical stakeholders through clear visualizations, reports, and presentations.
Collaborate with stakeholders to ensure that datadriven insights are effectively integrated into decisionmaking processes and drive measurable business outcomes.

-
Maintenance of ML Models and Platform:

Maintain machine learning models on the Data Lake platform, ensuring their reliability, scalability, and performance over time.
Implement monitoring mechanisms to track model performance, detect drift, and facilitate timely updates or retraining as needed.

-
Continuous Learning and Innovation:

Stay updated on the latest developments in data science techniques, tools, and technologies through continuous learning and selfimprovement.

Required Skills/Abilities:

Education Qualification:

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

Work Experience:

At least 25 years of relevant work experience in data science or a related field.

Skills Requirement:

-
Solid Understanding: A strong foundation in statistics, mathematics, and probability theory.
-
Programming Proficiency: Proficiency in the Python programming language.
-
Data Manipulation and Visualization: Experience with data manipulation libraries such as Pandas and NumPy, and data visualization tools like Matplotlib, Seaborn, and PowerBI.
-
Machine Learning: Familiarity with machine learning techniques and frameworks such as scikit-learn, TensorFlow, and PyTorch.
-
SQL Proficiency: Strong SQL programming experience is essential. Knowledge of Teradata is desirable.
-
Cloud Platforms: Understanding of ML cloud platforms like AWS SageMaker, Google Cloud AI Platform, or Microsoft Azure Machine Learning is a plus.
-
Analytical Skills: Strong analytical and problem-solving skills with attention to detail.
-
Communication and Collaboration: Excellent communication and collaboration skills, as the role involves working closely with cross-functional teams.

We recognize and reward your hard work through a competitive compensation and performancebased incentive.
We empower you to learn and grow through training that gives you the knowledge, skills, and abilities to develop into your role and a great range of resour