Lead Data Scientist

Role: Lead Data Scientist

Location: Bengaluru & Chennai (Hybrid)

Experience: 5-8 years

Company Overview:

Akaike Technologies is a dynamic and innovative AI-driven company dedicated to building impactful solutions across various domains. Our mission is to empower businesses by harnessing the power of data and AI to drive growth, efficiency, and value. We foster a culture of collaboration, creativity, and continuous learning, where every team member is encouraged to take initiative and contribute to groundbreaking projects. We value diversity, integrity, and a strong commitment to excellence in all our endeavors.

Job Description:

We are looking for a Lead Data Scientist to join our team, with a focus on driving innovative solutions using cutting-edge AI/ML and LLM technologies. This role demands a blend of deep technical expertise, team management skills, and strategic client engagement. The ideal candidate will have a proven track record in designing and deploying scalable AI/ML solutions, managing data science teams, and managing end-to-end client solutions. They will be responsible for building advanced models, mentoring teams, and delivering high-impact data science projects.

Key Responsibilities:

1. Team Mentorship:

Lead, mentor, and develop a team of data scientists and ML engineers, fostering a culture of collaboration and innovation.

Provide guidance and technical direction, helping the team navigate

complex problems and project delivery.

2. AI/ML Solution Development:

Design and implement advanced machine learning models and

algorithms tailored to various use cases across different domains, such

as Pharma, BFSI, and beyond.

Drive innovation by exploring new techniques in areas like structured data modeling, explainable AI, and large-scale language models (LLMs).

3. Client and Stakeholder Management:

Serve as the primary point of contact for client communications,

translating complex data requirements into actionable tasks.

Present data-driven insights to stakeholders, demonstrating the business impact of models and solutions.

Collaborate with cross-functional teams to align AI initiatives with

business goals.

4. Project Delivery and Strategy:

Lead multiple R&D POC projects, accelerating development and ensuring successful productization and deployment.

Define project timelines, ensure timely delivery, and continuously optimize project processes.

Translate the business problem into a data science problem by identifying key objectives, data requirements, and performance metrics.

Then, develop a scalable solution architecture that addresses both the technical challenges and the business nuances.

Provide a solution design with clear steps for junior data scientists to follow, alongside a robust system design for the architecture to ensure

scalability, reliability, and performance at larger scales

5. Platform and Product Development:

Spearheaded the development of IP-driven solutions, ensuring scalability, cost-efficiency, and ease of use for internal and client teams.

Drive continuous improvements to existing platforms and products to enhance performance and scalability.

Key Qualifications & Skills

Must Have Skills:

Technical Skills:

1. At least 5 years of experience developing machine-learning methods
2. At least 5 years of experience building Deep learning models in NLP, CV, or other domains
3. Deep understanding of data analysis, machine learning, deep learning, clustering and classification techniques, and algorithms
4. 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)
5. 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.
6. 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.
7. Deep familiarity with at least one cloud platform and its tools for developing solutions and deployment eg. AWS, Azure, or Google Cloud Platform

Soft Skills:

1. Excellent leadership and mentoring abilities, with a proven track record of managing and growing data science teams.
2. Strong analytical and problem-solving skills, with a proactive approach to overcoming challenges.
3. Excellent communication and presentation skills, with the ability to translate complex technical concepts into business-friendly language.
4. Experience in client engagement, managing multiple projects simultaneously, and delivering on tight deadlines.
5. Experience in cross-functional collaboration with departments such as marketing, pre-sales, and R&D.

Good to Have Skills:

Technical Skills:

1. Familiarity with big data frameworks (e.g., Hadoop, Spark) and visualization tools (e.g., Tableau, PowerBI).
2. Experience with platform development and creating scalable AI solutions in a startup environment.

Soft Skills:

1. Experience hiring and leading Senior Data Scientists
2. Experience ideating and implementing platforms and products for accelerated Data Science solutions
3. Experience working in a startup as an initial core contributor
4. Experience publishing and presenting work at conferences, seminars, and workshops

Benefits and Perks

Competitive ESOP grants with faster vesting periods

Leading a team and working on services & initiatives independently

An opportunity for hiring & training people to drive the value they create

Opportunity and budget to go to networking events, conferences, and seminars

Visibility on all the functions at Akaike including sales, pre-sales, lead generation, marketing, and hiring