Last updated on: 22rd Jan, 2024.
Contact: minesh.1291@gmail.com, LinkedIn, Kaggle, Github, My Blog
🚀 Innovative Data Scientist & Cloud Architect Extraordinaire
As a seasoned Data Scientist, Cloud Solution Architect, and Machine Learning Algorithm Research Engineer, I bring a wealth of experience in crafting cutting-edge solutions. With a track record as Kaggle Competition Expert #553 (Top 0.5%), I've honed my skills in developing algorithms, statistical models, and deep learning architectures in high-performance Big Data environments.
🔍 Unraveling TimeSeries Mysteries in IoT
Currently immersed in the TimeSeries (IoT) domain, I orchestrate machine learning experiments and engineer efficient sequence models for Time-Series anomaly detection, segmentation and classification. With over 9 years of hands-on experience, I thrive on tackling complex challenges in Data Science & AI.
🛠️ Tech Alchemist & Problem Solver
As a versatile developer and researcher, I wield expertise in data mining, visualization, modeling, and evaluation using Python, Pyspark, and R on Cloud Platforms. Fluent in SQL and Java, I thrive on adapting to new ideas, concepts, methods, and technologies, always eager to push the boundaries.
🌐 From Algorithms to APIs: Cloud-Based Excellence
My journey includes solving interdisciplinary data problems, designing scalable algorithms/models, and crafting data science APIs in a cloud-based environment. Seeking opportunities in sequence modeling for TimeSeries, NLP, Computer Vision, and discrete optimization across diverse domains.
🌐 Computational Sciences Maestro
Delving into realms like BioMarker Identification, Drug Target Identification, Cancer Genomics, Viral Genomics, and more, I specialize in predictive modeling across diverse computational sciences.
📩 Let's Connect and Innovate!
For consultancy or exciting positions, reach out at minesh[dot]1291@gmail.com. Curious minds are always welcome. Ping me for the full CV.
🌍 Global Vision, Indian Heart
By nationality, I am Indian and ready to be sponsored for a work permit in other countries.
📈 Data Science & AI Expertise
I'm well-versed in the entire Data Science lifecycle, from data collection and cleaning to model development and deployment. I've also developed a strong background in the following areas:
| - Machine Learning & Deep Learning - Time-Series Analysis - Reinforcement Learning - Natural Language Processing - Computer Vision - Genomics & Transcriptomics - Computational Biology - Data Visualization - Cloud Computing - Big Data - Data Engineering - DevOps - Software Engineering - Agile Methodologies |
Experience
Lead / Senior Data Scientist
DatAIsm (Full-time) Sep, 2021 - Present India
Lead Data Analyst & Data Scientist
Recruitment Smart (Full-time) Jan, 2021 – Sep, 2021 India
Data Engineer & Cloud MLOps Consultant
Freelancer (Contracts) June, 2020 – Jan, 2021 India
Senior Data Scientist
YOUTILIGENT (Full-time) Dec, 2018 – June, 2020 Israel
At Youtiligent, a trailblazer in IoT-based solutions for the food and beverage industry, I played a pivotal role in revolutionizing data analytics. As a key contributor, my responsibilities included:
🛠️ Algorithm Design and Optimization
I spearheaded the design and optimization of robust algorithms tailored specifically for time-series data within the dynamic landscape of the Internet of Things (IoT). My focus extended to segmentation, clustering, and classification, leveraging advanced signal processing techniques.
🌐 IoT Signal Processing and Feature Engineering
With a keen eye on innovation, I delved into the intricacies of IoT sensor devices, extracting meaningful insights through meticulous signal processing. Additionally, I implemented advanced feature engineering strategies to enhance the quality and depth of our data analysis.
🚀 Driving Efficiency through Data Insights
My efforts were dedicated to not only unraveling complex time-series patterns but also to drive efficiency in the food and beverage industry. By harnessing the power of data, I contributed to elevating Youtiligent's position as a leader in delivering actionable insights. This experience fortified my expertise in developing tailored solutions within the IoT realm and honed my skills in algorithmic design and optimization for real-world applications. Youtiligent served as a dynamic playground where innovation and practicality converged to shape the future of IoT-based solutions in the food and beverage sector.
Bioinformatics Ph.D.
Ben Gurion University of the Negev March, 2016 – March, 2019 Be'er Sheva, Israel
At Ben-Gurion University, my tenure as a researcher was dedicated to unraveling the intricate relationship between the immune system and cancer progression. Key highlights of my contributions include:
🌱 Immuno Normalization of Expression Profiles
I actively engaged in the groundbreaking field of immuno normalization, harnessing its potential to bring clarity to the complex landscape of cancer-related gene expression profiles. This involved meticulous normalization techniques, ensuring a comprehensive understanding of immune system dynamics within the context of cancer.
📊 Feature Extraction and Selection
Utilizing advanced feature extraction methods, I sought to identify key patterns and markers crucial for understanding the nuances of the immune system's involvement in cancer. Precision in feature selection was paramount, aiming to uncover meaningful insights that could pave the way for personalized therapeutic interventions.
🔄 Dimensionality Reduction Strategies
Navigating the vast dimensionality of data, I applied innovative dimensionality reduction methods to distill complex information into manageable structures. This not only enhanced the interpretability of our findings but also paved the way for streamlined analyses, fostering a deeper understanding of the immune-cancer interplay.
🎯 Improving Prognosis and Patient Stratification
My research had a direct impact on improving cancer prognosis and patient stratification. By deciphering the immune system's influence on personalized therapeutic responses and recurrence patterns, I contributed to advancing our ability to tailor interventions based on individual patient profiles.
💡 Shaping the Future of Cancer Research
Ben-Gurion University provided an inspiring environment for delving into the forefront of cancer research. My role in exploring the immune system's role in cancer progression was not only intellectually stimulating but also contributed to the broader scientific community's understanding of personalized medicine and prognostic advancements.
Bioinformatics Researcher
ICGEB Full-time March, 2014 – March, 2016 New Delhi, India
My tenure as a researcher at the International Centre for Genetic Engineering and Biotechnology (ICGEB) was marked by engaging projects that spanned diverse aspects of genomics and bioinformatics for Agricultural Insights and Biofuel Advancements. Here's a snapshot of my impactful contributions:
🌾 NGS Data Analysis of Meta-Transcriptome from Rice Borer Gut Bacteria
At the intersection of genomics energy and agriculture, I spearheaded Next-Generation Sequencing (NGS) data analysis to unravel the meta-transcriptome of gut bacteria in rice borers. This endeavor wasn't just about deciphering microbial interactions; it was a catalyst for optimizing biofuel potential.
⚙️ Bridging Agriculture and Bioenergy
By connecting the dots between agricultural processes and the potential for biofuel production, our research at ICGEB aimed to bridge the gap between these seemingly disparate fields. The data-driven insights from our NGS analysis served as a foundation for devising strategies to optimize biofuel production processes.
📊 Database & Tool Development for Prokaryotic Transcriptional Factor Annotation
Contributing to the bioinformatics landscape, I led the development of databases and tools dedicated to annotating prokaryotic transcriptional factors. This initiative facilitated streamlined analysis and interpretation of genomic data, fostering a deeper understanding of transcriptional regulation in prokaryotic organisms.
🌱 Comparative Genomic Analysis for Plants and Prokaryotes
My research extended into the realm of comparative genomics, where I conducted analyses spanning both plant species and prokaryotic organisms. This holistic approach aimed to identify shared genomic features, evolutionary patterns, and potential functional implications, bridging the gap between diverse biological kingdoms.
🧬 Characterization of Ribo-Switch Regulation in Cyanobacterial Species
Delving into the regulatory mechanisms of cyanobacterial species, I focused on characterizing Ribo-Switch regulation. This involved unraveling the intricate controls governing gene expression, shedding light on the fascinating world of post-transcriptional regulation in photosynthetic microorganisms.
🌍 Global Impact: Advancing Sustainable Bioenergy
This research, situated within a privileged institution serving UN organizations, exemplifies the global impact of our work. Beyond advancing scientific knowledge, our focus on optimizing biofuel processes demonstrates a commitment to addressing global challenges and contributing to the development of sustainable bioenergy solutions.
My time at ICGEB was marked by a dedication to innovative research at the intersection of agriculture and bioenergy, with a vision to reshape the future of sustainable fuel production.
Bioinformatics Research Student
National Institute Of Virology 2013 – 2014 Pune, India
Illuminating Influenza Dynamics
As a research student at the National Institute of Virology (NIV), a distinguished World Health Organization (WHO) collaborating center for arbovirus and hemorrhagic fever reference and research, I engaged in impactful projects that advanced our understanding of influenza dynamics. Here's an overview of my contributions:
🌐 WHO Collaboration: Center for Arbovirus and Hemorrhagic Fever Reference and Research
Being part of NIV, a WHO collaborating center, I was immersed in the epicenter of arbovirus and hemorrhagic fever research. This affiliation underscored the global significance of our work, contributing to the WHO's mission in tackling infectious diseases.
💻 Web-Based SNP Database for Influenza Drug Resistance
I led the development of a cutting-edge web-based Single Nucleotide Polymorphism (SNP) Database tailored for tracking influenza drug resistance. This initiative aimed to streamline the accessibility of crucial genetic information, enhancing our ability to monitor and respond to the evolving landscape of influenza strains.
🦠 Evolutionary Dynamics of Influenza: Pandemic to Post-Pandemic
My research delved into the evolutionary trajectory of influenza, spanning both pandemic and post-pandemic periods. Through meticulous analysis, I sought to unravel the genetic nuances that shaped the virus's adaptability and persistence, contributing valuable insights for future preventive strategies.
📊 Statistical Analysis of Genetic and Proteomic Variants in Influenza
A significant aspect of my work involved performing detailed statistical analyses of genetic and proteomic variants within influenza's structural proteins. This approach provided a comprehensive understanding of the molecular intricacies governing the virus's behavior, with implications for antiviral drug development and treatment strategies.
🌍 Demographic Distribution Analysis of Influenza Infection
In addition to molecular investigations, I conducted analyses to scrutinize the demographic distribution of influenza infections. This holistic perspective aimed to uncover patterns and trends in the prevalence of influenza, informing public health strategies and interventions.
🌟 Contributing to Global Health through NIV
My experience at NIV was not just confined to a laboratory; it was a journey of contributing to global health. By unraveling the genetic and demographic facets of influenza, I played a role in fortifying NIV's position as a bastion of infectious disease research with far-reaching implications for public health worldwide.
🚀 Interests: A Multifaceted Exploration in Computational Sciences
My professional journey is propelled by a profound passion for diverse domains within computational sciences. Here’s a glimpse into my areas of interest and expertise:
Sequence Modeling: Delving into the intricacies of sequences, I am enthusiastic about applying advanced techniques in TimeSeries, Natural Language Processing (NLP), and Computer Vision to unravel patterns and insights.
Digital Signal Processing, Audio Processing, Computer Vision - Image Processing: A confluence of signal processing and computer vision captivates me. From refining digital signals to unraveling visual information, I seek to harness these disciplines for innovative applications.
Genomics, Transcriptomics, Systems Biology: The biological realm intrigues me, and I am drawn to unraveling the complexities of genomics and transcriptomics. Exploring systems biology allows me to understand the interconnectedness of biological processes.
Discrete Optimization for Operations Research: Crafting optimal solutions for operational challenges is a puzzle I love solving. The intersection of discrete optimization and operations research is where efficiency meets strategy.
Data Science, Artificial Intelligence, Data Mining: From mining valuable insights to crafting intelligent solutions, my interest lies in the synergy of data science and artificial intelligence, with a focus on practical applications.
Machine Learning, Deep Learning: The dynamic landscape of machine learning and deep learning fuels my desire to stay at the forefront of evolving technologies, pushing boundaries in predictive modeling and pattern recognition.
Problem Solving and Algorithm Designing: I thrive on dissecting complex problems and architecting elegant solutions. The process of algorithm design is where creativity meets precision.
Visualization & Storytelling: Transforming raw data into compelling narratives is a skill I cherish. Visualization not only communicates insights effectively but also adds a storytelling dimension to the analytical process.
🌐 Open to Opportunities in Computational Challenges:
I am actively seeking opportunities in sequence modeling for TimeSeries, NLP, Computer Vision, and discrete optimization across diverse domains, including biomedical, IT product, operations research, supply chain, or the energy sector. My passion lies in contributing to transformative projects that push the boundaries of computational sciences.
🌟 Hashtags: #DataScientist #MachineLearningEngineer #DevOps #MLOpsEngineer #CloudArchitecture #DataEngineer #SoftwareEngineer #DataScienceConsultant #ResearcherAndAnalyst
🔍 In the Computational Sciences:
Exploring the intricacies of computational sciences, I am particularly interested in areas such as BioMarker Identification, Drug Target Identification, Cancer Genomics, Viral Genomics, Geospatial Prediction, and beyond. These diverse domains inspire me to contribute meaningfully to the advancements in computational research.
Feel free to reach out for collaborative endeavors or to explore how my diverse skill set can add value to your projects.
Publications
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Toren, D., Kulaga, A., Jethva, M., Rubin, E., Snezhkina, A. V., Kudryavtseva, A. V., … & Fraifeld, V. E. (2020). Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination. Aging Cell.
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Pandya, P., Jethva, M., Rubin, E., Birnbaum, R. Y., Braiman, A., & Isakov, N. (2019). PICOT binding to chromatin-associated EED negatively regulates cyclin D2 expression by increasing H3K27me3 at the CCND2 gene promoter. Cell death & disease, 10(10), 1-15.
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Singh, P., Kumar, N., Jethva, M., Yadav, S., Kumari, P., Thakur, A., & Kushwaha, H. R. (2018). Riboswitch regulation in cyanobacteria is independent of their habitat adaptations. Physiology and Molecular Biology of Plants, 24(2), 315-324.
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Singh, A., Jethva, M., Singla-Pareek, S. L., Pareek, A., & Kushwaha, H. R. (2016). Analyses of Old “Prokaryotic” Proteins Indicate Functional Diversification in Arabidopsis and Oryza sativa. Frontiers in Plant Science, 7.
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Samant, M., Jethva, M., & Hasija, Y. (2015). INTERACT-O-FINDER: A Tool for Prediction of DNA-Binding Proteins Using Sequence Features . International Journal of Peptide Research and Therapeutics, 21(2), 189-193.
Data Science Projects
📦 Reinforcement Learning (RL) & Optimization ┣ Resources Management ┃ ┃ ┃ ┣ 📂 Halite 3 by Two Sigma | Dec, 2018 | Info | Repo ┃ ┃ ┃ ┣ 📂 Santa's Workshop Tour 2019 | Jan, 2020 | Info | Repo ┃ ┃ ┃ ┗ 📂 Investment Portfolio Management ┃ 📦 Time Series ┣ Segmentation & Classification ┃ ┃ ┃ ┗ 📂 IoT Device Monitring & Event Tracking | 2019 - 2020 | Info ┃ ┣ Forecasting ┃ ┃ ┃ ┗ 📂 Weather forecast challenge | May, 2018 | Info | Repo ┃ 📦 Image Processing ┣ Segmentation & Classification ┃ ┃ ┃ ┗ 📂 yet to add... ┃ 📦 Natural Language Processing (NLP) ┣ Classification ┃ ┃ ┃ ┗ 📂 Toxic Comment Classification Challenge | March, 2018 | Info | Repo ┃ 📦 Machine Learning ┣ Tabular Problems ┃ ┣ Predictive Maintanance ┃ ┃ ┃ ┃ ┃ ┗ 📂 Telstra Network Disruptions | March, 2016 | Info | Repo ┃ ┃ ┃ ┣ QA Time Estimation ┃ ┃ ┃ ┗ 📂 Mercedes-Benz Greener Manufacturing | July, 2017 | <a href="https://www.kaggle.com/c/mercedes-benz-greener-manufacturing"-->Info</a> | Repo ┃ 📦 Risk Assessment ┣ Cancer Immunology ┃ ┃ ┃ ┣ 📂 Regulatory analysis of Gene Expression profiles as predictor of patient survival | article ┃ ┃ ┃ ┗ [citation] Pandya, P., Jethva, M., Rubin, E. et al. PICOT binding to chromatin-associated EED negatively regulates cyclin D2 expression by increasing H3K27me3 at the CCND2 gene promoter. Cell Death Dis 10, 685 (2019). https://doi.org/10.1038/s41419-019-1935-0 ┃ 📦 Data Science API ┃ ┗ 📂 Stock Movement Predictor Service
To be continued…