Data Scientist

Technology & Analytics

Remote

Worldwide

We are looking for a Data Scientist to build and deliver predictive analytics solutions across our client engagements. Working alongside a Senior Data Scientist and AI Leader, you will contribute to the full modelling pipeline – from data preparation and feature engineering through to model evaluation and insight communication. You are technically solid and genuinely curious about what the data is trying to say. You care about the business context behind a problem, not just how well a model scores, and you communicate your findings clearly to both technical and non-technical audiences.

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About the job

Key Responsibilities

What we expect from you

Build and validate predictive models across customer analytics domains – Churn, Propensity, Segmentation, Satisfaction, and Value modelling

Prepare clean, reliable feature sets from large, multi-source datasets using PySpark, Python, and SQL

Apply explainability techniques (SHAP, feature importance) and communicate model behaviour clearly to non-technical stakeholders

Track model performance metrics and contribute to monitoring and re-training plans

Collaborate with the senior team and engineering to support production deployment of models

Qualification

Must Haves:

Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field

4+ years of hands-on Data Science and Machine Learning experience in large enterprise or consulting settings

Proven delivery of at least one predictive model in production or an advanced PoC – in any customer, operational, or behavioural analytics domain

Strong logical reasoning – able to structure a problem, form a clear hypothesis, and communicate the approach and findings to non-technical audiences

Genuine business curiosity – you ask why a model matters, not just whether it performs

Solid Python (scikit-learn, XGBoost or LightGBM), working PySpark proficiency, and advanced SQL

MLflow or equivalent for experiment tracking and model versioning

Familiarity with at least one cloud or big data platform: OCI, Azure, AWS, GCP, or Databricks

Power BI or Tableau for analytical dashboards and insight communication

Nice to Have:

Exposure to regulated or data-rich industries such as financial services, insurance, telecom, or healthcare – where customer data is complex and high-stakes

Exposure to CX or survey platforms such as Medallia or Qualtrics

NLP or text analytics experience applied to survey, complaint, or free-text data

Prior experience in a consulting or client delivery environment

What you can expect from us

At New Metrics, we are committed to creating an inclusive, flexible, human-centric and supportive work environment.

When you join our team, you can expect:

1. Exceptional trust based culture that fosters inclusion, creativity, and innovation:

91% of employees feel engaged, reflecting our ongoing efforts to deliver the best in class employee experience

94% of our employees feel included and have a sense of belonging

94% of employees trust their manager

2. Collaboration with a passionate and high-performing team that values appreciation of individual attributes and diverse perspectives

3. Exposure to a global brand known for its commitment to excellence and making a difference in creating human value

4. A comprehensive focus on flexibility, wellness and result orientation in operation

5. Strong focus on life-long learning and continuous development, along with opportunities to enhance your skills and knowledge

6. Equal opportunities for growth and development, supported by subsidized professional qualifications and paid professional memberships to advance your career

7. A commitment to environmental sustainability, creating a positive impact on the world around us

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We are looking for a Senior Data Scientist to lead end-to-end delivery of predictive analytics solutions across our client engagements. You will own the full modelling lifecycle – problem framing, feature engineering, model build, and production handoff along with engaging directly with clients to turn analytical findings into decisions. Beyond delivery, you will set the technical bar for the team and mentor junior data scientists. The right person thinks like a business analyst as much as a data scientist. You ask why a problem matters before deciding how to solve it, and you know how to communicate complex work in plain language to stakeholders who don’t live in model metrics.

22nd April 2026

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