<ul>
<li style="margin-left:0px;">Strategic Collaboration: Partnering with stakeholders to deeply understand business objectives and translate them into robust data science strategies.</li>
</ul>

<ul>
<li style="margin-left:0px;">Model Development: Designing, developing, and implementing advanced machine learning and statistical models to tackle complex business challenges.</li>
</ul>

<ul>
<li style="margin-left:0px;">NLP for Semantic Enrichment:Applying Natural Language Processing (NLP) techniques to extract, classify, and semantically enrich unstructured building data points, working closely with ontology experts.</li>
</ul>

<ul>
<li style="margin-left:0px;">Data Preparation &amp; Exploration: Conducting in-depth exploratory data analysis, meticulous data cleansing, and insightful feature engineering to prepare datasets for analysis, including text-based data.</li>
</ul>

<ul>
<li style="margin-left:0px;">Insight Generation: Exploring and utilizing various data mining and machine learning techniques to extract valuable insights and discover hidden patterns from large datasets.</li>
</ul>

<ul>
<li style="margin-left:0px;">Predictive &amp; Prescriptive Solutions: Developing powerful predictive and prescriptive models, algorithms, and prototypes to directly support business decision-making.</li>
</ul>

<ul>
<li style="margin-left:0px;">IoT/IIoT Expertise: Applying your working knowledge of handling IoT and IIoT data, including traditional use cases like anomaly detection for multi-sensor systems.</li>
</ul>

<ul>
<li style="margin-left:0px;">Forecasting Mastery: Leveraging your hands-on experience in forecasting using both traditional machine learning methods and advanced Deep Neural Networks.</li>
</ul>

<ul>
<li style="margin-left:0px;">Statistical Rigor: Performing thorough statistical analysis, hypothesis testing, and A/B testing to rigorously evaluate the effectiveness of models and algorithms.</li>
</ul>

<ul>
<li style="margin-left:0px;">Cloud-Based ML Systems: Gaining hands-on experience in developing end-to-end machine learning systems on leading cloud-based platforms like AWS or Azure.</li>
</ul>

<ul>
<li style="margin-left:0px;">Effective Communication: Clearly communicating findings and insights to both technical and non-technical stakeholders through compelling reports, presentations, and data visualizations.</li>
</ul>

<ul>
<li style="margin-left:0px;">Deployment &amp; MLOps: Understanding and applying CI/CD processes in product deployment, ensuring seamless delivery of solutions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Technical Proficiency: Demonstrating an understanding of Dockerization and REST APIs for scalable and efficient deployments.</li>
</ul>

<ul>
<li style="margin-left:0px;">Continuous Learning: Staying abreast of the latest trends and advancements in data science, machine learning, AI, and NLP technologies, identifying opportunities to apply them to improve business outcomes.</li>
</ul>

<ul>
<li style="margin-left:0px;">Software Development: Engaging in hands-on software development, primarily with Python.</li>
</ul>

What You''ll Bring (Your Qualifications):

<ul>
<li style="text-align:start;">We''re looking for someone who can hit the ground running and grow with us!</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience: 5+ years of experience in data science and/or data analysis with a proven track record of successfully developing and deploying ML models and algorithms.</li>
</ul>

<ul>
<li style="margin-left:0px;">NLP Expertise: Demonstrated experience with Natural Language Processing (NLP) techniques, including text classification, entity recognition, topic modeling, and semantic search.</li>
</ul>

<ul>
<li style="margin-left:0px;">Education: A Master''s or Ph.D. degree in Data Science, Computer Science, Statistics, Applied Mathematics, Computational Linguistics, or a closely related quantitative field. (B.E. / M.Sc. / MCA / B. Tech in Computer Science / Applied Mathematics or related fields with a good academic record will also be considered.)</li>
</ul>

<ul>
<li style="margin-left:0px;">Programming Prowess: Strong hands-on programming skills in Python are essential, with experience in relevant NLP libraries (e.g., NLTK, spaCy, Hugging Face, Gensim).</li>
</ul>

<ul>
<li style="margin-left:0px;">Domain Knowledge: Exposure to the industrial engineering domain, building management systems, or experience working with structured/unstructured data in a complex domain is highly preferred. Experience with ontologies or knowledge graphs is a significant plus.</li>
</ul>

<ul>
<li style="margin-left:0px;">Tool Proficiency: Proficient in the use of various data science tools and libraries.</li>
</ul>

<ul>
<li style="margin-left:0px;">Analytical Acumen: Excellent analytical and statistical skills to derive meaningful insights.</li>
</ul>

<ul>
<li style="margin-left:0px;">Collaboration &amp; Proactivity: A collaborative, team-oriented attitude with a proactive mindset and a strong willingness to learn new technologies.</li>
</ul>

<ul>
<li style="margin-left:0px;">Communication Skills: Excellent verbal, written, and presentation skills to articulate complex ideas clearly. </li>
</ul>

Data Scientist

Strategic Collaboration: Partnering with stakeholders to deeply understand business objectives and translate them into robust data science strategies. Model Development: Designing, developing, and implementing advanced machine learning and statistical models to tackle complex business challenges. NLP for Semantic Enrichment:Applying Natural Language Processing (NLP) techniques to extract, classify, and semantically enrich unstructured building data points, working closely with ontology experts. Data Preparation &amp; Exploration: Conducting in-depth exploratory data analysis, meticulous data cleansing, and insightful feature engineering to prepare datasets for analysis, including text-based data. Insight Generation: Exploring and utilizing various data mining and machine learning techniques to extract valuable insights and discover hidden patterns from large datasets. Predictive &amp; Prescriptive Solutions: Developing powerful predictive and prescriptive models, algorithms, and prototypes to directly support business decision-making. IoT/IIoT Expertise: Applying your working knowledge of handling IoT and IIoT data, including traditional use cases like anomaly detection for multi-sensor systems. Forecasting Mastery: Leveraging your hands-on experience in forecasting using both traditional machine learning methods and advanced Deep Neural Networks. Statistical Rigor: Performing thorough statistical analysis, hypothesis testing, and A/B testing to rigorously evaluate the effectiveness of models and algorithms. Cloud-Based ML Systems: Gaining hands-on experience in developing end-to-end machine learning systems on leading cloud-based platforms like AWS or Azure. Effective Communication: Clearly communicating findings and insights to both technical and non-technical stakeholders through compelling reports, presentations, and data visualizations. Deployment &amp; MLOps: Understanding and applying CI/CD processes in product deployment, ensuring seamless delivery of solutions. Technical Proficiency: Demonstrating an understanding of Dockerization and REST APIs for scalable and efficient deployments. Continuous Learning: Staying abreast of the latest trends and advancements in data science, machine learning, AI, and NLP technologies, identifying opportunities to apply them to improve business outcomes. Software Development: Engaging in hands-on software development, primarily with Python. What You''ll Bring (Your Qualifications): We''re looking for someone who can hit the ground running and grow with us! Experience: 5+ years of experience in data science and/or data analysis with a proven track record of successfully developing and deploying ML models and algorithms. NLP Expertise: Demonstrated experience with Natural Language Processing (NLP) techniques, including text classification, entity recognition, topic modeling, and semantic search. Education: A Master''s or Ph.D. degree in Data Science, Computer Science, Statistics, Applied Mathematics, Computational Linguistics, or a closely related quantitative field. (B.E. / M.Sc. / MCA / B. Tech in Computer Science / Applied Mathematics or related fields with a good academic record will also be considered.) Programming Prowess: Strong hands-on programming skills in Python are essential, with experience in relevant NLP libraries (e.g., NLTK, spaCy, Hugging Face, Gensim). Domain Knowledge: Exposure to the industrial engineering domain, building management systems, or experience working with structured/unstructured data in a complex domain is highly preferred. Experience with ontologies or knowledge graphs is a significant plus. Tool Proficiency: Proficient in the use of various data science tools and libraries. Analytical Acumen: Excellent analytical and statistical skills to derive meaningful insights. Collaboration &amp; Proactivity: A collaborative, team-oriented attitude with a proactive mindset and a strong willingness to learn new technologies. Communication Skills: Excellent verbal, written, and presentation skills to articulate complex ideas clearly.

Data Scientist in Mumbai (UID-15330)

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