Data Scientist

Data Scientist (0?1 AI Systems) Bhashsms

Location: Bangalore (On-site)

Experience: 24 years

Compensation: ?1830 LPA

Role Type: Hands-on IC (no managers)

About the Role

Bhashsms is building Indias largest SME Engagement OS with AI-powered customer lists, campaign intelligence, and automated business growth.

We are looking for a hands-on Data Scientist who loves building 0?1 systems, not writing long research papers.

Your work will directly impact millions of campaigns executed by 510 lakh SMEs.

This is not a theoretical DS role.

This is a builders role.

What You Will Build (First 180 Days)

You will work closely with the CTO to build:

1. AI Targeting Engine (Core Project)

• Predict the best phone numbers for an SMEs campaign
• Build scoring models using our historical campaign data
• Create a lead-likelihood algorithm (LLA)

2. Campaign Effectiveness Score

• Predict campaign ROI
• Analyse delivery, open, click, reply, and business outcomes
  
• Build dashboards to help SMEs choose the best audience

3. Number Intelligence Graph

• Deduplicate, cluster, and classify 20M+ numbers
• Label type ? customer, dormant, likely buyer, spam, etc.
• Map SMEs to the right customer personas

Skills You Need

Must Have

• Strong Python (Pandas, NumPy, Scikit-Learn, FastAPI optional)
• SQL mastery
• Experience working with large datasets
• ML model building (classification, clustering, scoring systems)
• Basic understanding of feature engineering
• Strong analytical thinking

Good to Have

• PySpark experience
• Exposure to marketing analytics
• Worked on recommender systems
• Data scraping knowledge
• Basic MLOps
• Familiar with cloud (AWS/GCP/Azure)

We are looking for someone who:

• Learns fast
• Ships fast
• Takes ownership
• Is humble + hungry
• Loves experimentation
• Can handle ambiguity
• Wants to build something big in India

Responsibilities

• Own the AI data product end-to-end
• Build models that deliver real business impact
• Work with engineering to deploy your models
• Iterate weekly based on feedback
• Deliver measurable improvements in campaign ROI
• Maintain high-quality datasets and pipelines

Success Metrics

Your work is successful if:

• Campaign ROI increases
• SME retention increases
• Targeting accuracy improves monthly
• Model deployment time falls
• Net revenue per SME rises