Data Scientist - Big Data & AI
Location: Gurgaon, India
Role Responsibilities/Accountabilities:
- Collaborate with WWT business, engineering, and technology teams to align on data strategies.
- Extract data from customer source systems or databases and integrate it into software or development environments.
- Conduct Exploratory Data Analysis (EDA) and process data using programming tools such as Python.
- Analyze data and develop solutions to business problems using statistical and programming tools like Python.
- Perform quality control of deliverables to ensure accuracy and reliability.
- Prepare and present reports and presentations, showcasing findings effectively.
- Stay updated with advancements in Big Data, AI, Deep Learning (e.g., Spark, AWS, Azure ML, PyTorch), and Generative AI (e.g., Langchain).
- Provide thought leadership in algorithmic and process innovations, offering creative solutions to unconventional problems.
- Engage with clients, including in-person meetings, to make business recommendations and present findings with visual displays of quantitative information.
- Research and develop internal capabilities to enhance skill sets on the latest data science developments and produce innovative solutions.
Qualifications
Required:
- Basic understanding of supervised learning (e.g., linear and logistic regression, time series forecasting) and unsupervised learning algorithms (e.g., K-Means, K-NN).
- Fundamental knowledge of statistics and hypothesis testing.
- Programming experience in Python, R, or Java.
- Basic knowledge of databases and experience with SQL.
- Proficiency in functional and object-oriented programming (OOPS) concepts.
- Experience with MS tools (e.g., Excel, PowerPoint).
- Strong communication skills.
Preferred:
- Experience with Big Data platforms (e.g., Hadoop, Apache Spark, Hive, HBase).
- Academic or project experience with Deep Learning toolkits (e.g., TensorFlow, Keras, Theano, PyTorch, Caffe).
- Familiarity with UNIX-based systems and command-line utilities (e.g., sed, awk, Makefile).
- Experience working with NoSQL databases.