Global Data Analytics Expert at Valerie Group · Bengaluru (Bangalore) · 7 - 10 years · ₹25L - ₹40L / yr · Bootstrapped · Posted 19 Oct 2026
We are looking for a rigorous, systems-minded quantitative leader to own our core commercial intelligence engine end-to-end. This is not a traditional dashboard-building or BI reporting seat. You will define, build, and encode the mathematical logic, unit-economic models, and predictive forecasting systems that power our product and drive real commercial decisions for our brands.
You will sit at the intersection of finance, data science, and product engineering, turning complex commercial data, messy founder inputs, and predictive models into defensible, automated product logic and AI agent workflows.
Key Accountabilities
1. Proprietary Systems: Growth Forecasts & P&Ls
- Growth Forecasting: Build and own the methodology that takes a brand’s current performance and projects a defensible 12-month forecast, complete with a rigorous assumption set.
- Financial Architecture: Construct brand-level P&Ls directly from the forecast, mapping revenue, COGS, contribution margin, and operating costs.
- Variance & Calibration: Continuously run models against real outcomes, measure errors, track actuals against projections, and explain every variance.
2. Productization & Agentic Workflow Design
- Product Logic: Translate sophisticated financial and statistical models into production-ready product logic so the system calculates and delivers outputs natively.
- AI Agent Specification: Define what data agents compute, what internal data/benchmarks they draw on, and what assertions they are strictly barred from making.
- Human-in-the-Loop Orchestration: Replace manual validation with automated product rules while establishing clear review gates for human sign-off before deliverables ship.
- Data Schemas & Engineering Collaboration: Specify data structures, validation rules, and pipelines across structured commercial inputs, partnering directly with engineering to bring models to life in production.
3. Decision Framing & Commercial Rigor
- Decision-First Modeling: Design every analysis backwards from the specific commercial decision it is meant to change.
- Uncertainty & Stated Confidence: Size uncertainty statistically, state clearly what sparse or self-reported data cannot support, and attach a stated confidence level to every output.
- Benchmark Library Management: Define and version the benchmark repository (category, stage, market) to evaluate brands accurately even when data is sparse.
4. Enablement & Commercial Communication
- Cross-Functional Communication: Present complex numbers, models, and uncertainties to founders and operators with clarity and authority.
- Quantitative Literacy: Raise the analytical bar across the business by teaching teams how to read and interpret model outputs correctly.
- Documentation & Standards: Write airtight documentation and standards for data/finance deliverables so cross-functional delivery teams can execute autonomously.
What This Seat Is Not
- Not a BI/Reporting Seat: Dashboards are merely one downstream output of this work; your primary focus is proprietary modeling and product architecture.
- Not Research Without Action: We judge models by the decisions they actually changed, not academic complexity.
- Not a Data Engineering Seat: You will specify pipelines, schemas, and logic for engineering to build—you won't be maintaining core infrastructure tables yourself.
Ideal Background & Qualifications
Must-Haves
- Experience: 6–8 years in growth, marketing, commercial, or product analytics within DTC, e-commerce, marketplaces, or specialized platforms.
- Proven Track Record: End-to-end ownership of a forecasting, unit-economics, or media-mix model that commercial teams relied on for high-stakes budget or strategic decisions. You can name the decisions your model changed and what followed.
- DTC Unit Economics Mastery: Deep fluency in CAC, AOV, COGS, contribution margin, LTV, payback period, breakeven, retention cohorts, and working capital reconciliation.
- Modelling with Incomplete Data: Demonstrated ability to build robust outputs from banded, self-reported, or partial founder inputs while explicitly quantifying confidence levels.
- Statistical Rigor: Strong foundation in sizing uncertainty, managing sample limitations, and maintaining analytical integrity.
- Technical Depth: Hands-on daily fluency in SQL and Python.
- Product & Engineering Collaboration: Experience working directly with engineering teams to turn quantitative models or metric definitions into production software.
- Communication: Exceptional presence and ability to defend underlying assumptions and model uncertainty under direct challenge.
Nice-to-Haves
- Media mix modeling (MMM), incrementality testing, or causal measurement methodologies.
- Applied machine learning experience (forecasting, propensity, or segmentation models in production).
- Experience evaluating generative AI or multi-agent system outputs.
- Familiarity with modern data stack layers (Snowflake, BigQuery, dbt) and attribution platforms (Triple Whale, Northbeam, Rockerbox).
- Exposure to multi-brand ecosystems via agency, consulting, or platform environments.
- Experience in early-stage product environments where models and products were co-developed from scratch.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Valerie Group
About
Valerie is a launchpad for ambitious minds - builders, creators, and problem-solvers who don’t just follow the market but shape it. We believe founders and commerce fuel economies, drive opportunities, and create generational wealth - not just for individuals, but for families and communities worldwide. And we’re here to turn passion into impact.
We’re building a company that finds and backs high-potential founders- the ones overlooked by big capital, ignored by industry, or underestimated by the system. We partner with them to test, scale, and blow up their businesses. But to do that, we need the right people in our own ranks.
At Valerie, we’re built on fairness, talent, and performance - a team of operators who share the entrepreneurial spirit and grit of founders. If you’re driven by solving real problems and helping others scale, you’ll fit right in.
We believe in:
- Merit over politics
- Performance over outdated processes
- Skills over hierarchy
Join Us If You:
- Want to craft your skills alongside top experts in digital marketing, performance, creative, tech, investment, and capital funding.
- Prefer remote-first, high-autonomy work over being chained to a desk from 9-5.
- Thrive in a fast-moving, results-driven culture built for entrepreneurs, not bureaucrats.
We’re building for the bold - only those with the grit, ambition, and mindset of a founder. If that’s you, Valerie can take your career to the next level.
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- Build and integrate NLP-based solutions for text data analysis and insights.
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Required Skills:
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- Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
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- Advanced knowledge of SQL for data manipulation.
- Hands-on experience with Power BI for visualization and reporting.
- Expertise in advanced Excel (Power Query, dashboards, data modeling).
- Strong analytical and problem-solving skills.
Preferred Qualifications:
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We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
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What We’re Looking For
- Proven experience working as a Data Analyst or in a similar analytical role
- 5+ Years of experience in the field
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- Ability to communicate findings clearly to technical and non-technical stakeholders
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What You’ll Be Doing:
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Analytics & Dashboarding
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Leadership & Process Excellence
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Data SciencePythonRole Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
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Data Science & Machine Learning
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AI Solution Development
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Required Technical Skills
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- Knowledge of construction, engineering, manufacturing, or industrial domains.
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Soft Skills
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- Strong hands-on experience with Python and SQL.
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- Strong data analysis, hypothesis-generation, and problem-solving skills.
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- Experience with anomaly detection techniques such as Isolation Forest and Autoencoders.
- Experience building and deploying production ML solutions.
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Good to Have:
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Data SciencePython🚀 We’re Hiring | Data Scientist 🧠📊
Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!
🔹 Experience: 8+ Years
🔹 Must-Have Skills:
🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization
📍 Location: Pune
💼 Work Mode: Work from Office
If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!
📩 Interested? Kindly text
#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow
PythonData ScienceMachine Learning (ML)We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.
Key Responsibilities
- Develop and implement machine learning and predictive analytics models.
- Perform data analysis, statistical modeling, and optimization to solve business problems.
- Build demand forecasting and predictive models using time-series and other advanced techniques.
- Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
- Develop and maintain scalable data pipelines for ML model development and deployment.
- Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
- Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
- Validate models for accuracy, robustness, bias, and production readiness.
- Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.
Required Skills
- Python
- SQL
- Data Science & Machine Learning
- Predictive Modeling
- Statistical Analysis
- Machine Learning Algorithms
- Optimization Techniques
- Google Cloud Platform (GCP)
- BigQuery
- Dataflow
- Dataproc
- Data Fusion
- Cloud SQL
- Airflow
- PySpark
- PostgreSQL
- Terraform
- Tekton
- APIs
- MLOps
Preferred Skill
- Java
Good to Have
- Demand Forecasting
- Time-Series Analysis
- Neural Networks
- Ensemble Methods
- Support Vector Machines (SVM)
- Regression and Cluster Analysis
- ML Model Testing
- Bias Detection and Data Drift Monitoring
- Production ML Deployment
- QlikSense
- Automotive or Supply Chain Analytics
Education
Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.
PythonMachine Learning (ML)Description
We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.
Responsibilities
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- Hands-on experience with Databricks, Airflow, and AWS EMR.
- Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
- Solid understanding of query optimization, storage systems, and data pipelines.
- Excellent problem-solving skills, with the ability to design scalable solutions.
- Strong communication and collaboration skills to work in cross-functional teams.
Benefits
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- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
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About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
Data AnalyticsTitle : Marketing Analytics Specialist
Experience : 5 to 8 yrs
Location : Anywhere in India – Preferred Chennai
Type of Hire : PwD/Non PwD
Work type : Remote
Employment Type : Full Time
Notice Period : Immediate
Workday : Mon to Fri
Role Overview
We are looking for an experienced Marketing Analytics Specialist to derive actionable commercial insights from Reckitt’s cross-channel e-commerce sales data. The role involves integrating data from multiple, inconsistently structured sources, developing scalable data pipelines and data models, creating business intelligence dashboards, and analyzing the impact of media platform spending on sales performance across various retailer platforms.
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- Business Requirements: Collaborate with business stakeholders to understand reporting requirements and translate them into analytical solutions.
- Data Architecture: Design and implement efficient data storage, retrieval, and processing architectures.
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- Experience with data warehousing concepts and data modeling.
- Proficiency in Power BI, Tableau, or other BI visualization tools.
- Experience analyzing e-commerce sales, marketing performance, media spending, or retailer data.
- Knowledge of data quality, data validation, and reconciliation techniques.
- Strong analytical, problem-solving, and stakeholder communication skills.
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon