Data Scientist
2 weeks ago
We're Hiring: Data Scientist – Digital Transformation Organization
Company:
TC Consulting Services
Location:
100% Remote
Compensation:
Package – ₹10 LPA
Shift:
Night Shift (Mon–Fri, 9 AM – 5 PM EST, US Time)
TC Consulting Services is building a new
Digital Transformation Organization
, and we're looking for a passionate
Data Scientist
to join our journey. This team's mission is to leverage data to
boost productivity and revenue
, starting with our
"Modern Sales" initiative
.
Key Responsibilities
- Model Development & Evaluation
– Build, test, and optimize predictive models using ML/DL techniques (time-series, structured & unstructured data). - Data Analysis & Pipelines
– Perform EDA, feature engineering, and automate data/model pipelines using tools like
Databricks
or
Azure Data Factory
. - Generative AI & AI Agents
– Develop and fine-tune
LLMs, RAG systems, and AI agents
, with strong expertise in
prompt engineering
. - Collaboration & Communication
– Work cross-functionally with engineers and project managers to deliver insights and translate findings into business outcomes.
Required Skills
- Experience -
Minimum 3 years overall, with 2–3 years in AI/ML. - Python
– Hands-on expertise with Pandas, NumPy, Scikit-learn. - Machine Learning
– Proficiency in regression, classification, clustering, TensorFlow, PyTorch. - Generative AI
– Experience with OpenAI, Hugging Face, or similar frameworks. - Prompt Engineering
– Ability to design and optimize prompts effectively. - Data Pipeline Tools
– Skilled in orchestration frameworks (Databricks, Azure Data Factory). - Visualization
– Strong command of Matplotlib and Seaborn.
Why Join Us?
This is a
high-growth, fast-paced environment
where you'll be at the forefront of building AI-driven solutions that directly shape modern sales strategies. Our Digital Transformation Office is driving innovation by reimagining processes, enabling smarter decision-making, and creating
data-powered customer solutions
.
Interested? Apply now and be part of a team shaping the future of data-driven transformation
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