Data Scientist – ROAS Forecasting- Fulltime 3 Month Contract

Experience: 3.00 + years

Salary: USD 2222-2592 / month (based on experience)

Expected Notice Period: 15 Days

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

Opportunity Type: Remote

Placement Type: Full Time Contract for 3 Months(40 hrs a week/160 hrs a month)

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

What do you need for this opportunity?

Must have skills required:

Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL

PvX Partners is Looking for:

Data Scientist – ROAS Forecasting

Location: Remote

Experience: 3–4 years

Company: PvX Partners

About PvX Partners

PvX Partners is a global leader in performance marketing for mobile games and apps. We

combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns

for some of the world’s most innovative gaming and app companies. Our data intelligence

platform leverages advanced machine learning to analyze performance signals, benchmark

outcomes, and forecast returns, helping clients scale profitably and outperform their

competition.

At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be

part of a team that pushes boundaries at the intersection of technology, data, and marketing.

The Role

We are looking for a Data Scientist with 3–4 years of hands-on experience to drive

development of forecasting models for Return on Ad Spend (ROAS) across gaming and

consumer app companies. This is a high-impact role where you will analyze large-scale

marketing and monetization datasets, develop predictive models, and create evaluation

frameworks to guide investment decisions.

You’ll work closely with product, engineering, and finance teams to translate business goals

into robust, data-driven solutions. If you’re passionate about performance marketing,

forecasting models, and enjoy solving problems that are both technical and strategic—this

role is for you.

You Will

• Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1,
  
  
  

M3, M6, M12) using historical cohort performance data.

• Identify and incorporate leading indicators such as CPI, CTR, early retention (Day
  
  
  

1–Day 7), and channel mix, and lagging indicators such as cumulative revenue,

payback curves, and seasonal trends.

• Own the end-to-end modeling workflow: cohort creation, feature engineering,
  
  
  

model development, backtesting, and deployment.

• Develop model evaluation frameworks to assess prediction quality over
  
  
  

time—using metrics like MAPE, RMSE, and directionality accuracy.

• Build scenario-based tools that help stakeholders understand upside/downside
  
  
  

impacts of marketing spend on long-term returns.

• Customize modeling approaches across game genres, monetization strategies
  
  
  

(IAP vs IAA), and geographies—adapting to different client contexts.

• Collaborate with internal product, engineering, and client-facing teams to translate
  
  
  

forecasts into actionable investment decisions.

• Document assumptions clearly and drive continuous improvements to model
  
  
  

performance based on real-world feedback and new data.

You Need

• 3–4 years of experience building and deploying machine learning models, preferably
  
  
  

in marketing, gaming, or consumer tech domains.

• Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with
  
  
  

experience working with attribution data (MMPs like Appsflyer, Adjust, etc.).

• Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet,
  
  
  

PyMC3, or LightGBM).

• Experience in building and maintaining end-to-end data pipelines using SQL, Airflow,
  
  
  

or similar orchestration tools.

• Strong statistical intuition and experience with model evaluation techniques (e.g.,
  
  
  

cross-validation, backtesting, MAPE/RMSE).

• High degree of ownership, adaptability, and willingness to work across multiple client
  
  
  

contexts with varied problem statements.

• Bonus points for familiarity with monetization models (IAP vs IAA), channel-level
  
  
  

performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves

Engagement Type: 3 Month Fulltime Contract

Job Type: Contract

Location: Remote

Working time: 10:00 AM to 7:00 PM

Interview Process: 3 Rounds

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!