Data Scientist / ML Engineer - 2 Posts

Accreteinfo; India; On-site; INR 900,000 - 1,500,000; Full time

Benefits offered by this job

Intensive training

Competitive remuneration

Job summary

Accreteinfo is seeking a Data Scientist / ML Engineer to build demand and sales forecasting capabilities for enterprise supply-chain products. You will tackle production forecasting problems, including seasonality and cold-start issues, and deliver forecasts to planners via integrated applications.

The role requires 2–6 years of data science/ML experience, strong Python skills, and experience with forecasting libraries. SAP experience is a plus; work is on-site at Infocity Gandhinagar, Gujarat.

Qualifications

• Bachelor's or Master's in CS, Statistics, Data Science, or related field.
• 2–6 years of data science/ML experience with at least one real forecasting project.
• Strong Python (pandas, numpy, scikit-learn) and forecasting libraries like Prophet or statsmodels.
• SQL skills and ability to query relational databases.
• Experience building or consuming APIs for modeling deployment.
• Ability to explain modeling decisions to non-technical stakeholders.

Responsibilities

• Design and build demand/sales forecasting models for distribution planning.
• Handle seasonality, promotions, and cold-start forecasting issues.
• Build data pipelines to ingest ERP data (SAP a plus) and prepare it for modeling.
• Integrate forecasts into planning apps via APIs or scheduled jobs.
• Collaborate with analysts and clients to translate domain rules into features.
• Track model accuracy (MAPE, bias) and iterate based on outcomes.
• Create dashboards to explain forecast performance to stakeholders.
• Document models and ensure reproducible pipelines.

Skills

Python

Pandas

Numpy

Scikit-learn

Time-series

Forecasting

APIs

SQL

Communication

Education

Bachelor's or Master's in CS/Statistics/Data Science

Tools

Prophet

Statsmodels

LightGBM

XGBoost

Job description

Accrete believes in being a company that provides benefits and happiness to all of its employees. We foster an environment that appreciates each employee's effort and ensures that their worth is appropriately acknowledged through the best incentives, facilities, and career opportunities.

Innovation through continuous leaning and implementation is the key to our success. The pleasure factor of our staff is reflected in their effectiveness, and hence in Accrete's ever-growing success. If you, too, want to join the Accrete family and earn competitive remunerations, intensive training, and a sense of importance.

Data Scientist / ML Engineer (2-6 Years) ( Full Time )

Office No-1, IT Tower-1, Ground Floor, Infocity, Gandhinagar, Gujarat 382007

We're looking for a Data Scientist / ML Engineer to build demand and sales forecasting capability for our enterprise supply-chain and distribution planning products. You'll work on real production forecasting problems - predicting product-level demand across a distribution network, handling seasonality and promotional effects, and solving for products with little or no sales history - and you'll be responsible for getting those forecasts into the hands of planners through the applications our engineering team builds. This is a hands-on, build-from-scratch role: there's no existing forecasting pipeline to inherit. You'll define the approach, build it, and iterate with direct client feedback.

As a Data Scientist / ML Engineer, you'll need to:

• Design and build demand/sales forecasting models (time-series methods such as ARIMA/SARIMA, exponential smoothing, Prophet, as well as ML-based approaches like LightGBM/XGBoost) for distribution and replenishment planning use cases.
• Handle real-world forecasting challenges: seasonality, promotional and scheme effects, and cold-start forecasting for newly launched products with no sales history.
• Build data pipelines to ingest and clean sales, stock, and order data from enterprise ERP systems (SAP experience is a strong plus) and structure it for modeling.
• Integrate forecast outputs into downstream planning applications via APIs or scheduled jobs, working closely with backend developers.
• Collaborate with business analysts and client stakeholders to translate supply-chain domain rules and constraints into model features.
• Track and report model accuracy (e.g., MAPE, bias), and iterate models based on real business outcomes, not just offline metrics.
• Build simple dashboards/reports to explain forecast performance to non-technical business stakeholders.
• Document your modeling approach and keep pipelines reproducible and maintainable by the rest of the team.

Education & Experience Requirement

• Bachelor's or Master's degree in Computer Science, Statistics, Data Science, or a related field.
• 2-6 years of experience in data science or ML, including at least one real-world forecasting or time-series project (academic projects alone are not sufficient).
• Strong Python skills — pandas, numpy, scikit-learn — and familiarity with forecasting libraries such as Prophet, statsmodels, or equivalent.
• Solid grasp of time-series fundamentals: trend, seasonality, and how to approach cold-start/no-history forecasting problems.
• Working SQL skills and comfort querying relational databases directly.
• Experience building or consuming APIs to get model outputs into real applications — this role isn't notebook-only.
• Comfortable working directly with client stakeholders and explaining modeling decisions in plain business language.
• Comfortable in a small-team, multiple-hats startup environment.

Join us and be part of something bigger.