<ul>
<li style="margin-left:0px;">Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.</li>
</ul>

<ul>
<li style="margin-left:0px;">Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience on building session-level models, and analyze the high-volume clickstream data from digital platform.</li>
</ul>

<ul>
<li style="margin-left:0px;">Proven experience in developing sequence modeling using RNN, Transformers, LSTM, XG Boost, Decision trees, Bayesian networks, Random forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms and Dimensionality Reduction Algorithms.</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience in Deep Learning model development using Tensorflow, Keras, PyTorch</li>
</ul>

<ul>
<li style="margin-left:0px;">Hands on experience in building ML workflows</li>
</ul>

<ul>
<li style="margin-left:0px;">Fluent with Natural Language Processing and Text Analytics libraries (NLTK, SpaCy)</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience in Model implementation, Governance and monitoring.</li>
</ul>

<ul>
<li style="margin-left:0px;">Responsibilities include: Performing the code development of complex analytic algorithms and paradigms, perform a clear breakdown of the analytic functionality and separate it into working modules.</li>
</ul>

<ul>
<li style="margin-left:0px;">Working experience in Python, R and SQL</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience in Python data science packages such as numPy, SciPy and SciKit-learn</li>
</ul>

Nice to Have:

<ul>
<li style="margin-left:0px;">Experience with Data Science Platforms (Dataiku, H2o, Azure)</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience with one of Subversion/SVN, Git, GitHub, GitLab, Mercurial, or other version control system</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience with cloud platforms AWS, Azure, GCP a plus</li>
</ul>

<ul>
<li style="margin-left:0px;">Knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka</li>
</ul>

<ul>
<li style="margin-left:0px;">Familiar working in an AGILE environment</li>
</ul>

Education:

<ul>
<li style="margin-left:0px;">Bachelors degree or Master’s Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, Engineering etc.) or equivalent experience</li>
</ul>

<ul>
<li style="margin-left:0px;">Minimum 8-10 years of experience in data science and advance analytics. </li>
</ul>

Data Scientist

Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business. Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Experience on building session-level models , and analyze the high-volume clickstream data from digital platform. Proven experience in developing sequence modeling using RNN, Transformers, LSTM , XG Boost, Decision trees, Bayesian networks, Random forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms and Dimensionality Reduction Algorithms. Experience in Deep Learning model development using Tensorflow, Keras, PyTorch Hands on experience in building ML workflows Fluent with Natural Language Processing and Text Analytics libraries (NLTK, SpaCy) Experience in Model implementation, Governance and monitoring. Responsibilities include: Performing the code development of complex analytic algorithms and paradigms, perform a clear breakdown of the analytic functionality and separate it into working modules. Working experience in Python , R and SQL Experience in Python data science packages such as numPy, SciPy and SciKit-learn Nice to Have: Experience with Data Science Platforms (Dataiku, H2o, Azure) Experience with one of Subversion/SVN, Git, GitHub, GitLab, Mercurial, or other version control system Experience with cloud platforms AWS, Azure, GCP a plus Knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka Familiar working in an AGILE environment Education: Bachelors degree or Master’s Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, Engineering etc.) or equivalent experience Minimum 8-10 years of experience in data science and advance analytics.

Data Scientist in New Delhi (UID-15621)

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