Key Responsibilities: 

<ul>
<li style="margin-left:0px;"> Apply advanced forecasting methodologies to estimate sales and revenue for newly launched and pipeline pharmaceutical products (Demand Forecasting good to have skills). </li>
</ul>

<ul>
<li style="margin-left:0px;"> Incorporate financial modelling and corporate finance principles into forecasting frameworks to support long-term strategic planning. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Develop robust, data-driven models that incorporate market dynamics, patient behaviour, and competitive intelligence to generate accurate and actionable forecasts. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Collaborate cross-functionally with marketing, commercial, and research teams to ensure alignment of forecasts with strategic objectives and product positioning. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Leverage statistical, machine learning, and deep learning techniques to uncover insights that inform launch strategies and optimize product performance. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Partner with key business stakeholders to identify, scope, and execute predictive analytics initiatives that address critical business needs and deliver measurable value. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Maintain a strong understanding of the pharmaceutical landscape from financial operations to commercialization To provide objective, data-driven input into strategic decisions. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Collaborate within the analytics team, openly sharing knowledge and seeking feedback to enhance the quality and impact of analytical deliverables.</li>
</ul>
 
<ul>
<li style="margin-left:0px;"> Stay current with emerging techniques and tools in predictive analytics, ensuring methodological rigor and adaptability in approach. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Work comfortably with varied data sources and types, ensuring seamless integration and analysis across structured and unstructured datasets. </li>
</ul>

Requirements:

<ul>
<li style="margin-left:0px;"> Minimum of 5 years of working experience as a Data Scientist in industry. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Deep and broad knowledge of Data Science methods and tools including Simulation model building principles, Machine Learning, and best practices: </li>
</ul>

<ul>
<li style="margin-left:0px;"> Point Forecasting and Probabilistic Forecasting. </li>
</ul>

<ul>
<li style="margin-left:0px;"> Statistical Forecasting: ARIMA, THETA, Exponential Smoothing </li>
</ul>

<ul>
<li style="margin-left:0px;"> ML-based Forecasting: GBM, LightGBM, XGBoost, Linear Regression </li>
</ul>

<ul>
<li style="margin-left:0px;"> DL-based Forecasting: DeepAR, NBEATS, LSTM, RNN </li>
</ul>

<ul>
<li style="margin-left:0px;"> Hierarchical Forecasting </li>
</ul>

<ul>
<li style="margin-left:0px;"> Cross-Validation: Rolling-window, Expanding-window, K-fold, Hold-out </li>
</ul>

<ul>
<li> MLOps is also good to have skills. </li>
</ul>

<ul>
<li style="margin-left:0px;">Any type of simulation model experience (Good to have). </li>
</ul>

<ul>
<li style="margin-left:0px;">Agent-based Simulation Model using Anylogic (Good to have). </li>
</ul>

<ul>
<li style="margin-left:0px;"> Exposure to LLM or GPT good to have skills </li>
</ul>

Data Scientist

Key Responsibilities: Apply advanced forecasting methodologies to estimate sales and revenue for newly launched and pipeline pharmaceutical products (Demand Forecasting good to have skills). Incorporate financial modelling and corporate finance principles into forecasting frameworks to support long-term strategic planning. Develop robust, data-driven models that incorporate market dynamics, patient behaviour, and competitive intelligence to generate accurate and actionable forecasts. Collaborate cross-functionally with marketing, commercial, and research teams to ensure alignment of forecasts with strategic objectives and product positioning. Leverage statistical, machine learning, and deep learning techniques to uncover insights that inform launch strategies and optimize product performance. Partner with key business stakeholders to identify, scope, and execute predictive analytics initiatives that address critical business needs and deliver measurable value. Maintain a strong understanding of the pharmaceutical landscape from financial operations to commercialization To provide objective, data-driven input into strategic decisions. Collaborate within the analytics team, openly sharing knowledge and seeking feedback to enhance the quality and impact of analytical deliverables. Stay current with emerging techniques and tools in predictive analytics, ensuring methodological rigor and adaptability in approach. Work comfortably with varied data sources and types, ensuring seamless integration and analysis across structured and unstructured datasets. Requirements: Minimum of 5 years of working experience as a Data Scientist in industry. Deep and broad knowledge of Data Science methods and tools including Simulation model building principles, Machine Learning, and best practices: Point Forecasting and Probabilistic Forecasting. Statistical Forecasting: ARIMA, THETA, Exponential Smoothing ML-based Forecasting: GBM, LightGBM, XGBoost, Linear Regression DL-based Forecasting: DeepAR, NBEATS, LSTM, RNN Hierarchical Forecasting Cross-Validation: Rolling-window, Expanding-window, K-fold, Hold-out MLOps is also good to have skills. Any type of simulation model experience (Good to have). Agent-based Simulation Model using Anylogic (Good to have). Exposure to LLM or GPT good to have skills

Data Scientist in New Delhi (UID-14306)

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