Data Scientist

Founding Data Scientist / Quant Lead

Tessembl | Founding Data Scientist / Quant Lead

Location: [Mumbai / Hybrid]

Type: Full-time

Compensation: Competitive + meaningful ESOP

Apply: [Confidential Information]

About Tessembl

Tessembl is an early stage workforce intelligence company building data driven tools to help organisations make better people and workforce decisions.

We are combining behavioural science, workforce data, statistical modelling and machine learning to create a new generation of decision support software for organisations with large and distributed workforces.

We are currently building our founding team and are looking for a founding quantitative hire who can help shape the scientific foundation of the company.

The role

We are looking for a Founding Senior Data Scientist / Quant Lead to lead the development of our analytical and statistical methodology.

This is a hands-on founding role with significant influence over:

• model design;
• research methodology;
• data architecture;
• experimentation;
• validation;
• fairness;
• product analytics.

You will work directly with the founders, product team and behavioural-science specialists.

What you will do

• Design and develop statistical and machine-learning models for workforce decision support.
• Analyse employee, organisational and operational datasets.
• Develop robust approaches for prediction, ranking, benchmarking and longitudinal analysis.
• Design experiments and validation frameworks.
• Build appropriate measures of uncertainty and model confidence.
• Work with behavioural and psychometric data.
• Identify and control for confounding factors in real-world organisational datasets.
• Conduct model calibration, fairness and bias analysis.
• Develop methods for working with incomplete, noisy and heterogeneous enterprise data.
• Collaborate with engineering to productionise models.
• Translate complex analytical outputs into clear and explainable product insights.
• Help establish Tessembl's scientific standards and research methodology.
• Support early customer pilots and analyse real-world outcome data.

What we are looking for

• Strong background in statistics, data science, econometrics, quantitative psychology, applied mathematics or a related discipline.
• Strong Python and/or R capability.
• Excellent understanding of regression, classification and predictive modelling.
• Experience with model validation and out-of-sample testing.
• Ability to work with messy real world datasets.
• Strong understanding of correlation, causation and confounding.
• Familiarity with longitudinal or panel data.
• Ability to communicate quantitative findings clearly to non-technical stakeholders.
• Intellectual curiosity and willingness to challenge assumptions.

Particularly valuable experience

Experience in one or more of the following would be useful:

• multilevel or hierarchical modelling;
• survival analysis;
• Bayesian methods;
• causal inference;
• psychometrics;
• workforce analytics;
• behavioural science;
• recommender or matching systems;
• explainable AI;
• bias and fairness testing.

Why join

This is an opportunity to join at the beginning and help shape:

• the scientific architecture;
• the company's research agenda;
• the data strategy;
• future model development;
• the eventual data-science team.

We are looking for someone who wants to build the analytical foundation of a company, not simply maintain an existing model.