Staff Data Scientist
Outreach is hiring a Staff Data Scientist to join their AI platform team in Hyderabad. The role focuses on designing and implementing end-to-end machine learning systems, including GenAI applications, and building production-grade ML infrastructure. You will work cross-functionally to optimize customer engagement workflows through predictive analytics and natural language understanding. The position requires strong expertise in distributed data processing and microservices architecture.
50k new jobs listed every day. Install TAL to find more jobs like this.

Experience
7-10 years
Function
Research
Work mode
Onsite, India
Company
Tier 2
What you will work on
Outreach is hiring a Staff Data Scientist to join their AI platform team in Hyderabad. The role focuses on designing and implementing end-to-end machine learning systems, including GenAI applications, and building production-grade ML infrastructure. You will work cross-functionally to optimize customer engagement workflows through predictive analytics and natural language understanding. The position requires strong expertise in distributed data processing and microservices architecture.
TAL's take
High-level individual contributor role at a well-regarded SaaS company with clear ownership and technical requirements.
The JD clearly defines the role, team mission, daily responsibilities, and specific technical stack requirements.
Must haves
- Experience in machine learning application development end to end
- Experience developing and deploying GenAI based applications
- Experience building microservices
- Strong programming skills in object-oriented language
- Substantial experience building infrastructure for ML production deployment
- Experience with distributed data processing frameworks like Spark
Tools and skills
Nice to have: langchain, langgraph, spark mllib, aws, databricks, mlflow.
About the company
Outreach is an established US-based B2B SaaS company with significant scale, though it is not a top-tier FAANG/Unicorn status firm in the Indian market context.
Posts mentioning Outreach
Title: Data Scientist (~2 YOE) – Built planning tools, pipelines, and AI system. Need honest feedback on profile.
Hi all, Looking for practical feedback on my profile before I start applying. I’ll keep this structured so it’s easier to evaluate. --- 1) Planning Tools / Web Applications Problem: Forecasting workflows were fragmented and heavily Excel-driven: - Multiple data sources (orders, shipments, different forecast versions) - Manual merging, lookups, and adjustments - No way to simulate scenarios or compare forecasts cleanly - Different planners using different methods → inconsistency What I built: - Two internal applications for planning workflows: - A planning tool integrating 8+ data sources - A forecasting simulator supporting multi-level editing (high → granular) Key capabilities: - Real-time scenario simulation - Side-by-side comparison of multiple forecast types - Hierarchical adjustments across levels - SQL write-back for persistence Scale: - Processes ~150K+ records per cycle - Used in monthly planning cycles by multiple teams Impact: - Removed fragmented Excel workflows - Enabled consistent decision-making across users - Reduced manual effort and improved visibility into forecast behavior --- 2) Automation & Data Pipelines Problem: Core workflows were manual and repetitive: - Multi-file Excel processing - Data cleaning + merging across systems - Version tracking errors - High effort per cycle (1–4 hours depending on workflow) What I built: - Multiple pipelines automating end-to-end workflows Examples: - Large-scale consolidation pipeline: - Input: ~1M+ rows across 20+ files - Output: clean, unified dataset (~75% reduction) - 2nd pipeline: - Replaced a 23-step manual process - Standardized inconsistent formats across datasets - 3rd automation processing: - Automated unpivoting, enrichment, and version tracking Impact: - Reduced processing time from hours → minutes per cycle - Eliminated manual errors (copy-paste, lookup mistakes) - Standardized workflows across users --- 3) Power BI / Monitoring Problem: Recent data (orders/shipments) showed inconsistencies, but: - No visibility into changes over time - Hard to identify where data drift was happening What I built: - Power BI dashboards with: - Hierarchical filters - Drill-down views - Month-over-month comparison Scale: - ~30K+ records analyzed Impact: - Enabled early detection of data inconsistencies - Helped planners validate inputs before forecasting - Improved trust in upstream data --- 4) Side Project (AI System) What I built: - AI-powered job assistant system Features: - Scrapes job postings - Scores relevance using LLMs - Generates tailored resume points and outreach messages - Tracks applications Tech: - FastAPI backend - LLM routing (cloud + local fallback) - SQLite storage Goal: - Build a system-driven workflow (not just model usage) --- My concern Most of my work sits at the intersection of: - forecasting - data systems - workflow automation I’m trying to move into: 👉 Applied Data Scientist / Product-oriented roles --- Questions 1. Does this profile look too niche (forecasting-heavy)? 2. Does “building systems around data” help or hurt for DS roles? 3. What’s the biggest gap you see (if any)? Would really appreciate honest feedback. Thanks.
🚨 B2B Startups & Agencies 🚨
I have access to a special appolo.io API that lets me access unlimited leads. Comment if you want me to hit you up with unlimited leads at 5$ per 1000 leads Useful for SaaS, Start-ups, Marketing, Sales and Outreach (drop email to receive a sample)
How to enter into VC after 1.5 YoE in Mgmt Consulting
I am a Mechanical Engineer from one of the top IITs. Got a day 1 consulting job (tier 1 firm). It's been 1.5 years in the job and I want to switch to VC. Due promotion by the start of 2025. Recently interviewed with a new US based early stage VC firm (remote job), cleared the first interview and the case study, final interview didn't go amazingly well. They just wanted one Associate and I wasn't the best of the lot, got rejected. My job role actually says 'Business Analyst ' so I get outreaches for Analytics roles mostly. How do I enter into VC in India (early stage smaller fund-size VC firms preferred) ? What are the do's and don'ts? What would be the best time to target such roles? How should I prepare? Who should I reach out to and how? How should I shape my profile? Will it pay me as well as consulting? What are other options that I can consider apart from consulting (I was thinking about Strategy roles in startups/ founder's office). GV fam help me please!