Responsibilities:

<ul>
<li>Strategic Collaboration: Collaborate closely with product and business teams to gain a comprehensive understanding of the challenges and opportunities within the GenAI landscape, aligning data science initiatives with the organisation’s objectives.</li>
</ul>

<ul>
<li>Metric Definition: Define key performance metrics that accurately reflect the value delivered to end-users through GenAI solutions.</li>
</ul>

<ul>
<li>Intelligent System Design: Apply deep expertise in machine learning, statistics, and advanced mathematics to conceptualize, experiment, and design intelligent systems powered by GenAI.</li>
</ul>

<ul>
<li>Big Data Processing: Develop efficient systems capable of processing vast volumes of data, demonstrating proficiency in distributed programming frameworks like Hadoop and Spark.</li>
</ul>

<ul>
<li>ML/AI Architecture: Collaborate closely with ML Engineers to design scalable systems and model architectures that enable real-time ML/AI services.</li>
</ul>

<ul>
<li>End-to-End ML Pipelines: Take ownership of ML pipelines from start to finish, encompassing data pre-processing, model generation, cross-validation, and feedback sharing.</li>
</ul>

Qualifications:

<ul>
<li>A Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, or a related field, with a minimum of 10 years of relevant work experience.</li>
</ul>

<ul>
<li>Strong problem-solving and programming skills, coupled with a profound understanding of the mathematical foundations underpinning machine learning algorithms, including probability, statistics, linear algebra, calculus, and optimization.</li>
</ul>

<ul>
<li>Proven track record of successfully deploying ML projects in production systems with substantial individual contributions.</li>
</ul>


<ul>
<li>Experience with natural language processing tasks utilizing prompt engineering, LLMs, transformers, and knowledge graphs is highly advantageous.</li>
</ul>

<ul>
<li>Proficiency in time series analysis, NLP, Distributed Systems, large-scale computing, and Big Data technologies such as Spark is a plus.</li>
</ul>

<ul>
<li>A solid background in at least 3 of the following areas: Natural language processing, statistical ML techniques, graph algorithms, constraint optimization, signal processing (speech or vision), deep learning, and distributed systems.</li>
</ul>

<ul>
<li>Proficiency with database systems and schema design, encompassing both SQL and NoSQL databases. </li>
</ul>

Data Scientist in Chennai (UID-11471)

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