Senior Data Scientist

Job Brief
The Senior Data Scientist is responsible for transforming complex business problems into scalable Machine Learning and AI solutions. You will navigate the entire End-to-End ML Lifecycle, from initial business discovery and the extraction of insights from datasets to the deployment of high-performance models in cloud and on-prem environments.
In this role, you will act as a technical bridge, collaborating closely with Data Engineering to ensure robust data pipelines and with Business Intelligence (BI) teams to translate model outputs into actionable, executive-level insights. Beyond traditional predictive modeling, you will explore and implement Agentic AI frameworks to enhance system autonomy and reasoning. You must be adept at communicating technical complexities to cross-functional partners, ensuring every solution is production-ready and directly addresses key organizational challenges.

VentureDive Overview
Founded in 2012 by veteran technology entrepreneurs from MIT and Stanford, VentureDive is the fastest-growing technology company in the region that develops and invests in products and solutions that simplify and improve the lives of people worldwide. We aspire to create a technology organization and an entrepreneurial ecosystem in the region that is recognized as second to none in the world.

Key Responsibilities:

• Problem Transformation: Translate complex business challenges into technical AI/ML solutions.
• EDA & Hypothesis Testing: Conduct deep-dive exploratory data analysis to validate business assumptions and identify hidden patterns.
• Model Development: Design and train high-performance predictive models and ML algorithms tailored to business KPIs.
• Deployment & Scaling: Operationalize models for both real-time and batch scoring in cloud and on-prem environments.
• MLOps & Automation: Develop automated CI/CD pipelines to manage the full ML lifecycle and version control.
• Production Monitoring: Implement proactive monitoring for data drift and establish automated retraining protocols.
• Cross-Functional Synergy: Collaborate with Data Engineering for feature optimization and BI teams for executive-level data storytelling.
• Technical R&D: Research and prototype emerging technologies like model quantization and small language models (SLMs).
• Governance: Maintain rigorous technical documentation, operational procedures, and model performance logs.

Required Technical Skills:

• Programming: Python (Expert), SQL (Expert), or R.
• ML/DS: Scikit-learn, Pandas, pyCaret, statsmodel, ML algorithms & libraries (supervised & unsupervised)
• Deep Learning: PyTorch, TensorFlow, or Keras.
• Cloud: Azure ML, GCP or AWS (SageMaker, bedrock)
• MLOps & DevOps: Azure DevOps, GitHub Actions, MLflow, or DVC.
• Visualization: Power BI, Tableau, Plotly, or Streamlit.
• Nice to have:
  - LangChain or LlamaIndex; Hugging Face (Transformers/PEFT); Langraph and Vector Databases (Milvus, Qdrant, or Pinecone).
   - OpenAI API, Vertex AI (Gemini), or Azure AI Studio.

Qualifications & Experience

• Industry Expertise: 4+ years of professional experience in Data Science and Machine Learning, with a preference for candidates who have delivered use cases in Telecommunications (e.g., Demand Forecasting, Procurement Analytics) or Service-Oriented sectors (e.g., KPI optimization and Operational Risk Mitigation).
• Complex Data Handling: Proven track record of working with "messy" or disconnected datasets to extract high-value insights and validate business hypotheses.
• End-to-End Delivery: Expert at building, deploying, and maintaining ML pipelines and predictive models in production environments.
• Business Systems Integration: Hands-on experience manipulating and mining data from core business systems such as ERP, HRMS, CRM, or Supply Chain solutions.
• Agentic & Gen AI Exposure: Experience developing and deploying Generative AI use cases, specifically focusing on RAG and Agentic AI frameworks.
• Unstructured Data Mastery: Strong proficiency in processing and extracting value from unstructured sources, including logs, text, and sensor data.
• Cloud & Cross-Functional Collaboration: Extensive experience implementing ML solutions via Cloud (Azure, AWS, or GCP) while collaborating with Data Engineering, DevOps, and Business Stakeholders to deliver end-to-end products.

What we look for beyond required skills
In order to thrive at VentureDive, you
…are intellectually smart and curious
…have the passion for and take pride in your work
…deeply believe in VentureDive’s mission, vision, and values
…have a no-frills attitude
…are a collaborative team player
…are ethical and honest

Are you ready to put your ideas into products and solutions that will be used by millions?
You will find VentureDive to be a quick pace, high standards, fun and a rewarding place to work at. Not only will your work reach millions of users world-wide, you will also be rewarded with competitive salaries and benefits. If you think you have what it takes to be a VenDian, come join us ... we're having a ball!

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