It's fun to work in a company where people truly BELIEVE in what they are doing!

Retail SME
[Location; Mumbai]

Job Description:
Role Details

Brief about the Team & Fractal:
Fractal Analytics is a global pure-play analytics firm, founded in 2000. Today, we serve 75+ clients (60+ Fortune clients) across 100+ countries. We have a presence in 17 global locations, with headquarters in the World Trade Center, New York. We have delivery and consulting centres across Americas (San Mateo, Chicago, Toronto, New York), Europe (London, Amsterdam, Kiev, Geneva, Munich) and APAC ( Mumbai, Bengaluru, Gurugram, Pune, Chennai, Shanghai, Singapore, Sydney).
Our locations in India (Mumbai, Bangalore, Gurugram) and Europe (Kiev) act as scaled delivery and new capability development centres. Fractal is servicing clients across industries including Financial Services including buy-side, Insurance, Technology, Healthcare, Life Sciences, Retail, CPG, Government etc., and has very strong horizontal practice areas such as Artificial Intelligence & Machine Learning, Integrated Marketing Effectiveness, Big Data & Visualization, Digital Analytics, Supply Chain, Customer Analytics, FP&A analytics, Talent Analytics, Contact centre Analytics and IT Analytics.

Technical and domain expertise:
Technical – Python, ML
Domain – Retail

Role: Retail SME

The team member is expected to work directly with the client in a fast-paced working environment to address their day-to-day analytics requirements. The role will be an Offering Lead for the Account.

The indicative areas of work could be:
Marketing Effectiveness Measurement, Campaign Management and Spend Planning
Market Mix Modeling
Route to Market Analytics
Price & Promotion Planning
Innovation & Emerging Trend Analytics – Online/Offline Channels
Experience in Merchandising analytics will be preferred

Responsibilities:
Client management:
Lead the conversation with the client, stitch new ideas and opportunities, develop deep understanding of the client business, nature of work and building valuable and scalable solutions
Work with unstructured, complex, and even ambiguous use cases & carve out powerful solutions
Open to working in high pressure, slightly unstructured environments
Ability to strike meaningful business conversations with stakeholders across levels, geographies and roles
Ability to work with cross-functional teams in flexible time zones.

Technical:
Work with large, complex data sets to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed
Work on end-to-end data science problems – scoping, solution designing, data collection, EDA, statistical modelling, insight generation, model monitoring and deployment
Apply statistical tools and algorithms to identify and evaluate the data/factor/variable relationships testing business hypothesis and analyze outputs to recommend the next best action
Work on refactoring existing ML solutions to make them more efficient and/ or use them to build tools for other teams
Work on creating data driven business recommendations in the form of Power point presentations

Project management:
Lead multiple client engagements independently– driving thought leadership and delivery adherence on projects
Manage a team of 5-10 consultants, data scientists and engineers working on different projects across the account. Use structured project governance methods and own end-end deliverables
Spearhead client updates & meetings, manage technical/non-technical stakeholders, track engagement success metrics effectively & efficiently (Timelines, NPS, Project Margins, Utilization).

Qualifications & Experience:

Overall 8-11 years of total experience

Minimum of 4+ years of relevant experience in Retail
Strong experience in quantitative & qualitative analysis (root-cause analysis, causal modelling, forecasting, text mining, optimization)
Excellent problem solving, insight generation and stakeholder management skills coupled with strong communication/articulation skills
Must have mid-sized teams on client engagements
Good programming experience in Python, SQL, MS tools.

Experience in Merchandising analytics will be preferred

Education:
B.E/B.Tech/M.Tech in Computer Science/ ECE or Masters (MBA/MS) in any quantitative discipline

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!