As a Data Scientist, you will play a key role in turning complex data into actionable insights that drive business decisions. You will collaborate with cross-functional teams to identify opportunities, conduct rigorous analyses, and develop scalable solutions to achieve business objectives.
Required Skills
- 5+ years of experience in Data Science
- Excellent knowledge and experience of Python and SQL
- Strong interest in exploring all aspects of data and possess the ability to communicate insights effectively, while also concentrating on the technical solutions underlying them.
- Proficient in analysing and modelling big data utilizing statistical, machine learning, and deep learning techniques.
- Expertise in transforming ambiguous questions into impactful experiments, analysis, or models.
- Familiarity with modelling requirements for Customer 360 and Customer Journey.
- Experience with Machine Learning platforms (AWS Sage maker, Databricks), Data Pipelines (Spark, Airflow), CI/CD, GitHub, and visualisation (Power BI/Tableau).
- Have a degree in a quantitative field such as Computer Science/Engineering, Mathematics, Statistics, or Economics, with an advanced degree being desirable.
- Must have worked hand-on in the delivery of 1-2 scale projects.
- Must understand the nuances of Software delivery.
- Must understand and have worked on Data Engineering platforms
Job Responsibilities
- Utilise machine learning and deep learning models to create consumer intelligence, such as Next Best Action, Behaviour Models, and Churn, for customer-centric business teams.
- Write production level test driven code in Python and SQL.
- Analyse large datasets to uncover insights that inform marketing and customer-centric investments.
- Plan and execute experimentation initiatives, ensuring cross-functional alignment, robust analysis, and practical insights.
- Develop data-driven products that provide clear insights and recommendations to non-technical audiences through visualisations and presentations.
- Work collaboratively with product managers, senior scientists, engineers, and other team members in an agile and scrum environment to fulfil modelling needs.
Preferred :
- Experience with deploying ML model in production.
- Proficient knowledge of and experience with analytics, knowledge base construction, with particular focus on machine translation, and transformers.
- Proficiency with exploratory data analysis, statistics and working with unstructured textual data.
- Good to have, Experience with ML platforms such as Apache Spark, AWS Sage maker, Vertex AI, etc
- Experience with programming languages (eg: Java/Python, SAS) and SQL.
- Experience with Py Spark, and visualisation tools like Tableau, Excel, and PowerPoint.
- Experience working in AWS cloud.
- Knowledge of ML Ops will be an added advantage.
- Experience working with user Behavorial analytics.
- Knowledge of natural language processing tools such as NLTK, CoreNLP, Gensim, spaCy, OpenNLP, UIMA, GATE, etc
- Proficiency in machine learning tools such as TensorFlow, Keras, Caffe, Theano, MLLib, PyTorch, scikit-learn, etc
- Advanced experience in NLP, pattern recognition, predictive modeling, and evolving AI techniques.
- Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects.
