Data Scientist

Experience: 2.00 + years

Salary: Confidential (based on experience)

Expected Notice Period: 15 Days

Shift: (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type: Remote

Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: Yugen)

(*Note: This is a requirement for one of Uplers' client - Yugen)

What do you need for this opportunity?

Must have skills required:

auction/bidding environments, Data Studio, etc.)., Experience in ad tech / ad-serving / recommendation systems / marketplaces / personalization., Exposure to BI tools (Looker, Familiarity with click / conversion modeling, or revenue optimization., Ability to explain complex modeling and experiment results to non-technical stakeholders and client teams., Ad Recommendation & Ranking for the Client’s Product, Experience: 2–5 years as a Data Scientist working on production-facing ML problems., Experimentation & AB Testing, Model Development & Productionization (in GCP / AWS), NumPy, Programming: Strong Python skills; experience with ML libraries (pandas, Scikit-learn, XGBoost/LightGBM; PyTorch or TensorFlow).

Yugen is Looking for:

About The Role

We’re looking for a Data Scientist to work closely with one of our key clients operating in the

ad tech space. You will design, build, and iterate on recommendation and ranking systems

for their ad tech product, and help drive measurable impact through data, machine learning,

and experimentation.

You should be comfortable moving between data exploration, model prototyping, and

production realities in cloud environments (GCP / AWS), and be excited about running AB

tests to drive measurable impact on revenue and user experience.

You’ll collaborate with the client’s Product, Engineering, and Analytics teams, help shape

their roadmap, and translate business goals into robust data science solutions.You should be

comfortable with asynchronous communication (written updates, docs, Slack-style

collaboration) with both the client and our internal team across time zones.

What You’ll Work On

• Ad Recommendation & Ranking for the Client’s Product
  
  
  

○ Design and build ranking / recommendation models for the client’s ad tech

product (e.g., CTR / CVR prediction, EPC optimization, user–ad relevance).

○ Define and implement features from user behavior, campaign metadata,

device / context, traffic source, and historical performance.

○ Help the client evolve from simple ranking models to ML-driven

personalization and yield optimization.

• Experimentation & AB Testing
  
  
  

○ Design AB tests and online experiments to evaluate new models, ranking

strategies, targeting rules, and UI/UX changes.

○ Define and refine success metrics (CTR, CVR, EPC, ARPU, advertiser ROI,

retention, etc.) with client stakeholders.

○ Analyze experiment results, communicate findings clearly, and make

recommendations on rollouts.

• Model Development & Productionization (in GCP / AWS)
  
  
  

○ Prototype models in Python using standard ML / DL libraries (scikit-learn,

XGBoost/LightGBM, PyTorch / TensorFlow, etc.).

○ Contribute to offline and online evaluation frameworks (train/validation splits,

backtesting, shadow runs).

○ Work closely with the ML Engineer to:

■ Hand over model artifacts, feature definitions, and evaluation metrics.

■ Align on serving constraints (especially low-latency API

requirements and throughput).

■ Specify which features need to be available in an online feature

store for real-time scoring and ensure consistency between training

and serving.

○

• Data Analysis & Business Insights
  
  
  

○ Perform exploratory and statistical analyses on large log-level datasets

(impressions, clicks, installs/conversions, revenue).

○ Identify performance patterns across segments (geo, device, placement, user

cohorts, advertiser verticals).

○ Build and maintain dashboards and reports to track model performance, AB

tests, and key business KPIs.

○ Share findings via clear written updates and async communication

(decks, docs, Loom-style walkthroughs) with client stakeholders.

• Monitoring, Maintenance & Best Practices
  
  
  

○ Define what “good” looks like: KPIs, guardrails, and model health indicators.

○ Partner with the ML Engineer to set up monitoring/alerting for model

performance, data drift, and anomalies.

○ Lead root-cause analysis for performance regressions and propose

model/feature changes.

Key Qualifications

Must-Haves

• Experience: 2–5 years as a Data Scientist working on production-facing ML
  
  
  

problems.

• Programming: Strong Python skills; experience with ML libraries (pandas, NumPy,
  
  
  

scikit-learn, XGBoost/LightGBM; PyTorch or TensorFlow).

• Data: Strong SQL; comfortable analyzing large datasets in warehouses (BigQuery,
  
  
  

Redshift, Snowflake, etc.).

• ML Fundamentals: Solid understanding of supervised learning, feature engineering,
  
  
  

model evaluation (AUC, log loss, calibration, ranking metrics like NDCG / MAP), and

probability / statistics.

• Experimentation: Hands-on experience designing and analyzing AB tests / online
  
  
  

experiments (hypothesis setup, sample sizing, significance, confidence intervals).

• Communication:
  
  
  

○ Ability to explain complex modeling and experiment results to non-technical

stakeholders and client teams.

○ Comfortable with asynchronous communication in a remote/distributed

setup (writing good specs, documenting decisions, and keeping stakeholders

aligned over Slack/email/docs).

Nice-to-Haves

• Experience in ad tech / ad-serving / recommendation systems / marketplaces /
  
  
  

personalization.

• Familiarity with click / conversion modeling, auction/bidding environments, or revenue
  
  
  

optimization.

• Experience defining feature requirements and working with engineers on:
  
  
  

○ Feature stores, ETL/ELT, or streaming pipelines.

○ Model monitoring, alerting, and retraining workflows.

• Exposure to BI tools (Looker, Data Studio, etc.).
  
  
  

How to apply for this opportunity?

• Step 1: Click On Apply! And Register or Login on our portal.
• Step 2: Complete the Screening Form & Upload updated Resume
• Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
  
  
  

About Uplers:

Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.

(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!