JOB PROFILE

Job description

Fluency with Python, Database(MySQL/Postgres/MongoDB), Git versioning, Data Analysis Libraries(NumPy, Pandas, Statsmodels, Dask), Machine Learning Libraries( Scikit-learn), Deep Learning Libraries(Tensorflow/Keras/Pytorch), Data Visualization Libraries(Matplotlib, Plotly).

Responsibilities

• Analyse raw data: assessing quality, cleansing, and structuring for downstream processing.
• Design efficient and scalable AI solutions for a wide range of problems that generate actionable insights or automate the existing process. 
• Collaborate with the Data engineers, UI, and backend engineers to bring analytical prototypes to production. 
• Work with cross-functional teams to identify and understand business problems and develop data-driven solutions. 
• Communicate findings and insights to technical and non-technical stakeholders clearly and concisely. 
• Contribute or drive hiring, training & onboarding of new members to the team. 
• Participate in peer review of code and other technical work to ensure high-quality deliverables. 
• Stay up-to-date with the latest developments and trends in data science, machine learning, deep learning, NLP/LLMs, and applied ML domains.
• Technical Skills
• At least 4 years of experience developing machine-learning methods.
• At least 3 years of experience building Deep learning models in NLP, CV, or other domains.
• Deep understanding of data analysis, machine learning, deep learning, clustering and classification techniques, and algorithms 
• Fluency with Python, Database (MySQL/Postgres/MongoDB), Git versioning, Data Analysis Libraries(NumPy, Pandas, Statsmodels, Dask), Machine Learning Libraries( Scikit-learn), Deep Learning Libraries(Tensorflow/Keras/Pytorch), Data Visualization Libraries(Matplotlib, Plotly) 
• Understanding of and experience with NLP, CV, and Deep learning techniques including Word2vec, NER, topic modeling, ConvNets/ResNets/UNet, Mask-RCNN, RNNs/LSTMs, Transformers/BERT/T5/GPT-4, large-scale pretraining, contrastive learning, DL architecture design, and LLM finetuning among others. 
• Experience utilizing large-scale language models such as GPT-4 or other open-source alternatives (such as Mistral, Llama, and Phi-1) through prompt engineering and custom finetuning. 
• Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau) 
• Deep familiarity with at least one cloud platform and its tools for developing solutions and deployment eg. AWS, Azure, or Google Cloud Platform 
• Experience leading a team of data scientists, architecting solutions, and devising project plans. 
• Experience driving client engagement and problem discovery for multiple clients.
• Ability to manage multiple projects simultaneously and deliver results on time. 
• Strong communication skills and experience working with cross-functional teams.

Requirements

Optional and preferred qualifications 

• Experience publishing and presenting work at conferences, seminars, and workshops. 
• Experience collaborating cross-functionally with other departments including hiring, marketing, pre-sales, and R&D
• Experience hiring and leading Senior Data Scientists.
• Experience ideating and implementing platforms and products for accelerated Data Science solutions. 
• Experience working in a startup as an initial core contributor.