PythonRole Overview
We are seeking a hands-on technology POD Lead who blends engineering excellence with statistical rigor and business acumen to drive end-to-end product delivery in an agile, data-driven environment. The ideal candidate will lead a multidisciplinary team of BI developers, data engineers, ML practitioners, and product analysts to accelerate business growth through scalable, AI-enabled products, econometric models and intelligent insights.
This role sits at the intersection of engineering, analytics, econometrics, MLOps and growth strategy, requiring a balance of technical depth, stakeholder engagement, and agile execution.
Key Responsibilities
1. Leadership & Delivery
- Lead a cross-functional pod of data engineers, BI developers, statisticians and machine learning engineers to deliver AI-powered products and analytics solutions.
- Translate strategic goals into data science roadmaps executed in agile sprints, ensuring measurable business outcomes for every release.
- Foster a culture of experimentation, accountability, and rapid iteration across data, AI, and product workstreams.
2. Product & Business Integration
- Partner with business stakeholders across Sales, Marketing, Finance, and Operations to identify high-impact use cases such as churn prediction, growth forecasting, pricing optimization, causal impact analysis or next-best-action recommendations.
- Drive the roadmap for analytical and econometric product capabilities (e.g., predictive dashboards, personalization engines, time-series forecasting, and more).
- Ensure all solutions are aligned with enterprise data strategy, governance, MLOps lifecycle and security standards.
3. Technical Execution
- Collaborate with ML engineers to productionalize models using Databricks, MLflow, Azure ML, or equivalent CI/CD MLOps frameworks.
- Guide teams on feature engineering, model selection, hyperparameter tuning, and validation for statistical and machine learning models.
- Encourage adoption of reusable data assets, API-based integrations, and modular code frameworks.
- Oversee econometric modeling, causal inference studies, and time-series forecasting for business-critical decision-making.
- Champion model lifecycle management, including version control, retraining pipelines, and performance drift monitoring.
4. Business Intelligence & Data Storytelling
- Supervise the creation of advanced BI dashboards and insight layers powered by predictive and generative AI.
- Translate complex statistical outputs into actionable business narratives for executive decision-making.
- Champion KPI alignment and measurement frameworks, ensuring analytics deliver quantifiable value to revenue, growth, retention, and operational efficiency metrics.
5. Agile Program Management
- Manage sprint planning, backlog prioritization, and resource allocation across concurrent projects.
- Track velocity, quality metrics, and ROI impact for each product stream.
- Coach teams on agile best practices and outcome-oriented delivery.
Qualifications
Required
- 10+ years of total experience with at least 3 years in a tech lead capacity.
- Proven expertise in Python, SQL, statistical modeling (e.g., regression, time-series, causal inference) and one or more of Power BI, Tableau, MicroStrategy.
- Strong foundation in data engineering, cloud architecture (Azure/AWS/GCP), and ML model deployment.
- Experience leading cross-functional agile teams with engineers, analysts, and data scientists.
- Excellent communication and stakeholder management skills — capable of simplifying complex data stories for business leaders.
Preferred
- Experience in forecasting models, econometrics, and experimental design (A/B testing, uplift modeling).
- Exposure to MLOps tools (MLflow, Kubeflow, Airflow, Azure ML pipelines) and monitoring frameworks for models in production.
- Familiarity with agentic AI, LLM-based product development, or generative analytics use cases.
- Prior experience building analytics or AI solutions in B2B, SaaS, or digital transformation contexts.
- Certifications in Agile, Cloud (Azure ML, AWS Data Analytics), or Data Science specialization are a plus.
Key Traits
- Hands-on technologist who can code, review, and guide with empathy.
- Strategic thinker who connects product vision with execution.
- Comfortable operating in ambiguity and scaling solutions from POC to enterprise rollout.
- Passionate about mentoring teams and embedding a data-first, growth-oriented mindset.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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Full Stack Developer - Averlon