Manager/Senior Manager - Analytics - IT

Diversity Hiring - Analytics Manager /Sr Manager

Analytics -Manager/Sr Manager

Exp- 7-16 yrs

Work location - Work from home

Required Skills :

Successful candidates will have demonstrated the following skills and characteristics :

- Expertise in analytics in retail, CPG, technology, media, healthcare, lifescience, supply chain, hospitality, manufacturing and industrial products industries in the areas (but not limited to) customer analytics, pricing, promotion and profitability analytics marketing analytics, churn/attrition/retention analytics

- Supply chain and inventory optimization, ad sales effectiveness, digital channels effectiveness, market mix modelling, marketing attribution, revenue growth management

- Advanced level programming in Python, Pyspark and R

- Expertise in machine learning, supervised and unsupervised learning, time series analysis, optimization and simulation techniques

- Expertise in any one of the visualization tools such as Tableau, Power Bi, QlikView, Spotfire etc.

- Experience on working on any of the cloud platforms, Azure, AWS, Google Cloud

- Experience on deploying machine learning models in a client environment or on the cloud will be an added advantage.

- Ability to handle large volumes of data and derive meaningful business insights from them

- Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product.

- Ability to think through complex user scenarios and design simple yet effective solutions

- Extremely good communication skills, ability to handle client interactions independently, and good stakeholder management skills

Roles and Responsibilities :

Leadership :

- Ability to embed analytics into business solutions

- Help the Analytics Practice make a bigger impact in Firm's overall positioning in the market, through developing proof of concepts, point of views, thought leadership, whitepaper generation.

- Work closely with the Analytics Practice leadership in leading the team and develop capabilities, growing the team, and developing a pool of data scientists