Advanced Analytics Consultant

Project Role: Machine Learning Engineer

Work Experience: 2 to 4 Years

Work location: Bengaluru

Work Mode: Hybrid

Must Have Skills: Machine Learning, Statistical modelling, Clustering, Segmentation

Principal Accountabilities:

• Develop a good understanding of consumer offerings, proprietary databases, and analytical approaches to effectively guide and support client-facing stakeholders across globe
• Handle small and large datasets on projects efficiently and figure out the right technology for processing the data (e.g. Python, R, SAS etc.,). Be a champion on analytics technologies within the team
• Handle projects such as Segmentation & Targeting of Pharmacies/Physicians/Hospitals, Promotional Return (ROI analysis), Resource and Price Optimization analyses
• Present findings and recommendations to stakeholders in business point of view
• Ability to perform advance analytics using ML algo such as Linear & Non-Linear Regression, Hierarchical model, Bayesian, Time series, forecasting, RNN, CNN, LSTM, NLP etc.
• Provide support in building Data science/Advance Analytics proposals and presenting the same in front of leadership. Lead discussions and assess the feasibility of AI/ML solutions for business processes and outcome
• Ensure efficient and effective project delivery to meet project team and client expectations

Technical Skills Required:

• Proficiency in Python/R/SAS and MS office applications such as Excel and Power Point are mandatory; will be plus, if experience in data visualization platforms like Tableau, Power BI
• Commitment to work independently and collaboratively with others in and across team and organization to accomplish shared goal
• Highly motivated individual with zeal to learn new things and ready to take new challenges
• Good communication and presentation skills with focus on the technical aspects of a project and the ability to develop usable documentation
• Some experience in developing and deploying scalable AI/ML Solutions in the cloud (for example using Azure, AWS, GCP, Hadoop etc.,) and Generative AI will be a plus

Educational Qualification:

An academic background in quantitative sciences (Masters degree in Statistics, Mathematics, Economics/Econometrics or Bachelor’s degree in Computer Science, Data Science or AI/ML or related fields with a strong focus on quantitative analysis, including an acceptable number of courses in statistical methods and theory) from a well-known institution